410 lines
31 KiB
Python
410 lines
31 KiB
Python
"""Summarize observed research coverage; does not claim an exhaustive AI census."""
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import argparse
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from collections import Counter
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import json
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from pathlib import Path
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import sys
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from urllib.parse import parse_qs, urlsplit
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ROOT = Path(__file__).resolve().parents[1]
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DATA = json.loads((ROOT / 'content/research/ai-companies.seed.json').read_text())
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AUDIT = json.loads((ROOT / 'content/research/ai-companies.coverage.json').read_text())
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SOURCES = json.loads((ROOT / 'content/research/ai-companies.sources.json').read_text())
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TARGET = ROOT / '.artifacts/reports/02-coverage-and-gaps.md'
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SOURCE_SLUG = 'ai-company-research/02-coverage-and-gaps'
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BASE = '/docs/other-research/ai-company-research/overview'
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def yc_coverage_summary():
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companies = {row['id']: row for row in DATA['companies']}
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imported = [companies[f"YC{row['ycId']}"] for row in AUDIT['records'] if row['status'] == 'imported']
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profile_only = sum(bool(row.get('profileOnly')) for row in imported)
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groups = {}
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for label, prefix in [('unclearAI', 'YC-AI-UNCLEAR-'), ('missingYear', 'YC-MISSING-YEAR-'),
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('dateConflict', 'YC-DATE-CONFLICT-')]:
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rows = [row for batch in DATA.get('candidateBatches', []) if batch['id'].startswith(prefix)
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for row in batch['records']]
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groups[label] = {'records': len(rows), 'statuses': dict(sorted(Counter(row['status'] for row in rows).items()))}
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return {'initialProfiles': len(AUDIT['records']), 'originalImported': len(imported),
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'profileOnly': profile_only, 'deepenedOriginal': len(imported) - profile_only, **groups}
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def source_register():
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sources = SOURCES['sources']
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ids = {s['id'] for s in sources}
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assert len(ids) == len(sources) and ids == {f'S{i:02}' for i in range(1, 17)}
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assert SOURCES['scopeConfirmedAt'] <= DATA['asOf']
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host_map = {}
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for source in sources:
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assert source['status'] in {'candidate-audit', 'targeted', 'pending', 'context', 'access-limited', 'per-company'}
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assert source['boundary'] and source['nextCheck']
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if source['id'] == 'S01':
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assert source.get('coverageSummary') == yc_coverage_summary(), 'YC source summary is stale'
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if source['id'] == 'S14' and source.get('rosterAudit'):
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roster = source['rosterAudit']
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batch = next(batch for batch in DATA['candidateBatches'] if batch['id'] == roster['candidateBatchId'])
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assert batch['sourceId'] == 'S14' and not batch['complete']
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assert roster['defaultCohort'] == 'SR007' and roster['next'] is None
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assert len(batch['records']) == roster['recordCount'] == roster['reportedCount']
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assert len({row['url'] for row in batch['records']}) == roster['recordCount']
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if source['id'] == 'S14' and source.get('publicRosterAudits'):
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audits = source['publicRosterAudits']
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assert {a['cohort'] for a in audits} == {f'SR{i:03d}' for i in range(1, 8)}
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assert len(audits) == 7
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profile_urls = []
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for audit in audits:
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batch = next(b for b in DATA['candidateBatches'] if b['id'] == audit['candidateBatchId'])
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query = parse_qs(urlsplit(audit['url']).query)
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assert urlsplit(audit['url']).netloc == 'speedrun.a16z.com'
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assert query == {'limit': ['100'], 'offset': ['0'], 'cohort': [audit['cohort']]}
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assert urlsplit(audit['url']).path == '/api/companies/companyparams'
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assert audit['httpStatus'] == 200 and audit['accessedAt'] <= DATA['asOf']
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assert audit['next'] is None and audit['previous'] is None
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assert len(batch['records']) == audit['recordCount'] == audit['reportedCount']
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assert audit['uniquePublicIds'] == audit['uniqueSlugs'] == audit['recordCount']
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assert len(audit['responseSha256']) == 64 and all(c in '0123456789abcdef' for c in audit['responseSha256'])
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assert batch['sourceId'] == 'S14' and not batch['complete']
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proof = next(e for e in DATA['evidence'] if e['id'] == audit['evidenceId'])
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assert proof['url'] == audit['url'] and proof['companyId'] is None
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profile_urls.extend(row['url'] for row in batch['records'])
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assert len(profile_urls) == len(set(profile_urls)), 'duplicate profiles across public cohorts'
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if source['id'] == 'S14' and source.get('profileAudit'):
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audit = source['profileAudit']
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entries = audit['records']
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candidates = {row['id']: row for b in DATA['candidateBatches'] for row in b['records']}
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evidence_by_id = {row['id']: row for row in DATA['evidence']}
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assert len(entries) == audit['recordCount'] == audit['readable']
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assert audit['failed'] == 0 and len({e['candidateId'] for e in entries}) == len(entries)
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years = Counter(str(e['foundedYear']) for e in entries)
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assert dict(years) == audit['yearCounts']
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for entry in entries:
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row = candidates[entry['candidateId']]
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proof = evidence_by_id[entry['evidenceId']]
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assert row['profileStatus'] == 'readable' and proof['url'] == row['url']
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assert entry['evidenceId'] in row['evidenceIds']
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assert isinstance(entry['foundedYear'], int) and 1800 <= entry['foundedYear'] <= int(DATA['asOf'][:4])
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assert isinstance(entry['teamSize'], int) and entry['teamSize'] >= 0
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assert len(entry['htmlSha256']) == 64 and all(c in '0123456789abcdef' for c in entry['htmlSha256'])
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if entry['foundedYear'] not in [2025, 2026]:
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assert row['status'] == 'outside-cohort' and not row.get('companyId')
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assert sum(e['foundedYear'] not in [2025, 2026] for e in entries) == audit['outsideTargetYears']
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assert sum(e['foundedYear'] in [2025, 2026] for e in entries) == audit['targetYearSelfReports']
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assert sum(candidates[e['candidateId']]['status'] == 'linked' for e in entries) == audit['newLinkedCompanies']
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assert sum(candidates[e['candidateId']]['status'] == 'pending-ai' for e in entries) == audit['pendingCurrentAIOrIdentity']
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assert sum(candidates[e['candidateId']]['status'] == 'pending-year' for e in entries) == audit['pendingFoundingIdentity']
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assert audit['targetYearSelfReports'] == (
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audit['newLinkedCompanies'] + audit['pendingCurrentAIOrIdentity'] + audit['pendingFoundingIdentity']
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), 'self-reported years must retain unresolved brand/entity dates'
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if source['url']:
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assert urlsplit(source['url']).scheme in {'http', 'https'} and urlsplit(source['url']).netloc
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for host in source['hosts']:
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assert host not in host_map, f'Duplicate source host: {host}'
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host_map[host] = source['id']
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assigned = {key: [] for key in ids}
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for evidence in DATA['evidence']:
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owner = host_map.get(urlsplit(evidence['url']).netloc)
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if owner is None:
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owner = 'S12' if any(word in evidence['kind'] for word in ('官方', '公司自述', '公司披露')) else 'S16'
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assigned[owner].append(evidence)
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assert sum(len(v) for v in assigned.values()) == len(DATA['evidence'])
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statuses = {'candidate-audit': '候选池逐条已读', 'targeted': '定向使用，未穷尽', 'pending': '候选台账待建',
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'context': '背景研究', 'access-limited': '访问受限', 'per-company': '随公司逐条核对'}
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lines = ['', '## 来源清单与验收边界', '', SOURCES['provenance'], '',
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'每条证据在下表只计入一个渠道：先按所列域名归属，再将类型明确标为官方/公司自述/公司披露的剩余项计入S12，其余计入S16。公司可跨渠道出现，所以公司数不可跨行相加。零条证据表示尚未进入研究表，不表示该来源没有相关公司。背景报告不承担公司发现全集的角色。', '',
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'| 来源 | 当前状态 | 证据 / 公司 / 观测数 | 已核对范围 | 剩余核查 |', '| --- | --- | --- | --- | --- |']
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for source in sources:
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evidence = assigned[source['id']]
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evidence_ids = {e['id'] for e in evidence}
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company_ids = {e['companyId'] for e in evidence if e['companyId']}
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observations = sum(o['evidence'] in evidence_ids for o in DATA['observations'])
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name = f"[{source['name']}]({source['url']})" if source['url'] else source['name']
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boundary = source['boundary']
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if source['id'] == 'S01':
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summary = source['coverageSummary']
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boundary += (f" 当前原候选池{summary['initialProfiles']}项，原新增{summary['originalImported']}项中"
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f"{summary['profileOnly']}项目录基础资料、{summary['deepenedOriginal']}项深化个案。")
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for key, label in [('unclearAI', '原AI不明'), ('missingYear', '原缺年'), ('dateConflict', '原日期冲突')]:
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group = summary[key]
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labels = {'linked': '关联公司', 'pending-ai': 'AI主营待核',
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'pending-year': '成立/主体待核', 'outside-cohort': '范围外'}
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counts = '、'.join(f'{labels.get(status, status)} {count}' for status, count in group['statuses'].items())
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boundary += f" {label}{group['records']}项当前：{counts}。"
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lines.append(f"| {source['id']} {name} | {statuses[source['status']]} | {len(evidence)} / {len(company_ids)} / {observations} | {boundary} | {source['nextCheck']} |")
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lines += ['', 'Dealroom、Product Hunt、机器之心与36氪入口于2026-10-30重新访问。官网首页可读不证明已取得完整筛选结果；安全检测页面不作为文章内容。候选池之外的来源边界尚需建立可回查条目，完成前不宣布来源清单已全部覆盖。', '']
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return lines
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def context_methods():
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evidence = {e['id']: e for e in DATA['evidence']}
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rows = [s for s in SOURCES['sources'] if s.get('methodology')]
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assert {s['id'] for s in rows} == {'S06', 'S07', 'S08', 'S09'}
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lines = ['', '## 背景基准适用性与缺项', '',
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'以下核对背景资料的方法及适用范围，不是公司名录的完整覆盖。原始方法记录与全局核查随研究版本进入同一数据库；没有把行业汇总值新增为任何公司的收入观测。', '',
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'| 来源与证据 | 样本与统计单位 | 时间 | 本次读取范围 | 可用于什么 | 主要限制 |',
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'| --- | --- | --- | --- | --- | --- |']
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for source in rows:
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m = source['methodology']
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assert m['checkedAt'] <= DATA['asOf']
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assert all(m.get(key) for key in ('sample', 'unit', 'period', 'access', 'use', 'limit', 'evidenceIds'))
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assert all(eid in evidence and evidence[eid]['companyId'] is None for eid in m['evidenceIds'])
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assert not any(o['evidence'] in m['evidenceIds'] for o in DATA['observations'])
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proof = '、'.join(f"[{eid}]({evidence[eid]['url']})" for eid in m['evidenceIds'])
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lines.append(f"| {source['id']} {source['name']}：{proof} | {m['sample']}；{m['unit']} | {m['period']} | {m['access']} | {m['use']} | {m['limit']} |")
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lines += ['', '本表的应用解释属于研究判断。选样、分母、时间或指标不同会造成表观差异；这些差异不单独证明财务造假，也不能作为给未知公司填补收入的依据。', '']
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return lines
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def candidate_register():
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batches = DATA.get('candidateBatches', [])
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companies = {c['id']: c for c in DATA['companies']}
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categories = {c['id']: c['name'] for c in DATA['categories']}
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known_sources = {s['id'] for s in SOURCES['sources']}
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evidence = {e['id']: e for e in DATA['evidence']}
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assert len({b['id'] for b in batches}) == len(batches)
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all_ids = [r['id'] for b in batches for r in b['records']]
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assert len(set(all_ids)) == len(all_ids)
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lines = []
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statuses = {'pending-year': '成立年待核', 'pending-ai': 'AI主营待核', 'linked': '已关联公司',
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'existing-outside-cohort': '已有关联，年份范围外',
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'outside-cohort': '范围外或既有业务，不新增公司', 'promotion': '推广活动，非公司新增'}
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for batch in batches:
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assert batch['sourceId'] in known_sources
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assert batch['accessedAt'] <= DATA['asOf']
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assert any(e['url'] == batch['url'] for e in DATA['evidence'])
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rows = batch['records']
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counts = Counter(r['status'] for r in rows)
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assert sum(counts.values()) == len(rows)
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lines += ['', f"## {batch['sourceId']} 候选核对（{batch['id']}）", '',
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f"[发现页面]({batch['url']})，读取于{batch['accessedAt']}。{batch['scope']}", '',
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f"本批{len(rows)}条：{counts['linked']}条关联公司、{counts['existing-outside-cohort']}条关联范围外对照、{counts['outside-cohort']}条范围外不新增公司、{counts['pending-year']}条成立年待核、{counts['pending-ai']}条AI主营待核、{counts['promotion']}条推广活动。完整来源覆盖标记：{'已完成' if batch['complete'] else '未完成'}。主营或产品任务的初分类不计入主公司表数量，只有已关联的公司记录进入对应公司明细。候选与缺项随研究版本保存在文档站同一SQLite的研究元数据中。", '',
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'| 发现条目 | 主营或产品任务初分 | 核对状态 | 关联公司 | 核对证据 | 限制 |', '| --- | --- | --- | --- | --- | --- |']
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for row in rows:
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assert row['categoryId'] in categories
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assert row['status'] in statuses
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assert all(eid in evidence for eid in row.get('evidenceIds', []))
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if row['status'] in {'outside-cohort', 'pending-ai'}:
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assert row.get('evidenceIds') and not row.get('companyId')
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name = f"[{row['name']}]({row['url']})" if row['url'] else row['name']
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company = '—'
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if row.get('companyId'):
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assert row['companyId'] in companies
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c = companies[row['companyId']]
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company = f"[{c['name']}]({BASE}?company={c['id']}#research-company-detail)"
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proof = '、'.join(f"[{eid}]({evidence[eid]['url']})" for eid in row.get('evidenceIds', [])) or '成立证据待补，产品页读取状态见候选记录'
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category = f"[{categories[row['categoryId']]}]({BASE}?category={row['categoryId']})"
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lines.append(f"| {name} | {category} | {statuses[row['status']]} | {company} | {proof} | {row['note']} |")
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if batch['sourceId'] == 'S04':
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lines += ['', '产品页可读只表示有可访问的资料；本批未将所有产品页完成公司、技术或财务深查。既有直接HTTP采集返回403，当前采用可读的公开页面响应，不声称取得底层全量列表；后续公开档案与未读页面继续保留缺项。', '']
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else:
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lines += ['', '发现条目和可读正文分开记录；登录外壳、读取失败或搜索摘录不充当已阅读全文。关联公司以列出的原始材料补证，仍保留技术、主体与收入未核事项。', '']
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return lines
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def uncertain_ai_followups():
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original = {row['source']: row for row in AUDIT['records'] if row['status'] == 'ai-unclear'}
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rows = [row for batch in DATA.get('candidateBatches', [])
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if batch['id'].startswith('YC-AI-UNCLEAR-') for row in batch['records']]
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if not rows:
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return []
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urls = [row['url'] for row in rows]
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assert len(set(urls)) == len(urls), 'Duplicate AI-relevance follow-up URL'
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rechecks = {row['ycId']: row for row in DATA.get('directoryRechecks', [])}
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counts = Counter(row['status'] for row in rows)
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assert set(counts) <= {'linked', 'pending-ai'}
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for row in rows:
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assert row['url'] in original and row.get('evidenceIds')
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baseline = original[row['url']]
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if row['status'] == 'linked':
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assert rechecks[baseline['ycId']]['companyId'] == row['companyId']
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else:
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assert not row.get('companyId') and baseline['ycId'] not in rechecks
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unread = len(original) - len(rows)
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assert unread >= 0
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return ['', '## 原AI主营不明名单的后续覆盖', '',
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f"原名单{len(original)}项，已有后续记录{len(rows)}项：{counts['linked']}项关联公司、{counts['pending-ai']}项仍待核AI主营，{unread}项尚无本批系列的后续记录。计数按原始YC页面去重；EveryApp此前的独立复核与末批记录不重复相加。", '',
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'读完名单只证明每项有可回查的处理记录，不证明待核项均为AI公司，也不证明法律主体、收入或技术效果已独立验证。原始发现审计保持不变，成立年范围外/缺失、成立冲突及其他来源的缺项仍单列。', '']
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def founding_year_followups():
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original = {row['source']: row for row in AUDIT['records'] if row['status'] == 'date-conflict'}
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rows = [row for batch in DATA.get('candidateBatches', [])
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if batch['id'].startswith('YC-DATE-CONFLICT-') for row in batch['records']]
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urls = [row['url'] for row in rows]
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assert len(set(urls)) == len(urls), 'Duplicate founding-conflict follow-up URL'
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assert set(urls) <= set(original), 'Unknown founding-conflict follow-up URL'
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evidence = {row['id']: row for row in DATA['evidence']}
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for row in rows:
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assert row['status'] == 'pending-year' and not row.get('companyId')
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assert row.get('evidenceIds') and all(eid in evidence for eid in row['evidenceIds'])
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assert all(evidence[eid]['companyId'] is None for eid in row['evidenceIds'])
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unread = len(original) - len(rows)
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return ['', '## 原成立年冲突名单的后续覆盖', '',
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f"原名单{len(original)}项，已有后续记录{len(rows)}项，均保留成立年待核，{unread}项尚无本系列后续记录。当前业务初分类见候选表，不计入主公司表及收入统计。", '',
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'2025旧品牌发布可证明当时已有产品材料；当前目录的2026字段、批次、条款日期和运营者名称不能单独证明法律主体成立或新旧主体连续。未据此强改成立年。Layers当前AI核心仍另待核。', '']
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def missing_year_followups():
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original = {row['source'] for row in AUDIT['records']
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if row['status'] == 'year-outside-or-missing' and row['foundedYear'] is None}
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rows = [row for batch in DATA.get('candidateBatches', [])
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if batch['id'].startswith('YC-MISSING-YEAR-') for row in batch['records']]
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urls = [row['url'] for row in rows]
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assert len(set(urls)) == len(urls) and set(urls) <= original
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evidence = {e['id']: e for e in DATA['evidence']}
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for row in rows:
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assert row['status'] in {'outside-cohort', 'pending-year', 'pending-ai', 'linked'}
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assert row.get('evidenceIds')
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if row['status'] == 'linked':
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matches = [r for r in DATA.get('directoryRechecks', []) if r['companyId'] == row.get('companyId')]
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assert len(matches) == 1 and matches[0]['originalStatus'] == 'year-outside-or-missing'
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assert all(eid in evidence and evidence[eid]['companyId'] == row['companyId'] for eid in row['evidenceIds'])
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else:
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assert not row.get('companyId')
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assert all(eid in evidence and evidence[eid]['companyId'] is None for eid in row['evidenceIds'])
|
||
counts = Counter(row['status'] for row in rows)
|
||
return ['', '## 原缺少成立年名单的后续覆盖', '',
|
||
f"原快照缺年{len(original)}项，外部补核已有{len(rows)}项：{counts['linked']}项关联公司、{counts['outside-cohort']}项既有主体/业务范围外、{counts['pending-year']}项成立年待核、{counts['pending-ai']}项AI主营待核，{len(original)-len(rows)}项尚无本系列外部补核记录。", '',
|
||
'当前YC缺年字段复读与外部主体核查分别统计。登记创建日、公司自述年、产品发布、条款更新和批次不相互替代；已查英国或法国主体不代表完整集团沿革已核。原54项发现计数不回写，也不以Inactive补零收入。', '']
|
||
|
||
|
||
def directory_rechecks():
|
||
rows = DATA.get('directoryRechecks', [])
|
||
if not rows:
|
||
return []
|
||
original = {row['ycId']: row for row in AUDIT['records']}
|
||
companies = {c['id']: c for c in DATA['companies']}
|
||
evidence = {e['id']: e for e in DATA['evidence']}
|
||
assert len({row['ycId'] for row in rows}) == len(rows)
|
||
lines = ['', '## 原候选池的后续复核', '',
|
||
'原始1,428条读取快照与初筛计数保持不变；下表记录当时未入表、后续补足证据后进入公司表的项目。初筛未通过不是永久排除。后续入表不回写为当时已匹配，也不重复计入928条原始新增目录项。', '',
|
||
'| 原候选 | 原始状态 | 后续公司记录 | 复核证据 | 处理与限制 |', '| --- | --- | --- | --- | --- |']
|
||
for row in rows:
|
||
baseline = original[row['ycId']]
|
||
assert baseline['status'] == row['originalStatus']
|
||
assert row['reviewedAt'] <= DATA['asOf'] and row['reason']
|
||
assert row['originalStatus'] in {'ai-unclear', 'year-outside-or-missing', 'date-conflict'}
|
||
company = companies[row['companyId']]
|
||
assert row['evidenceIds'] and all(eid in evidence for eid in row['evidenceIds'])
|
||
proof = '、'.join(f"[{eid}]({evidence[eid]['url']})" for eid in row['evidenceIds'])
|
||
lines.append(f"| [{baseline['name']} · YC{row['ycId']}]({baseline['source']}) | {row['originalStatus']} | [{company['name']}]({BASE}?company={company['id']}#research-company-detail) | {proof} | {row['reviewedAt']}：{row['reason']} |")
|
||
lines += ['', f"已记录{len(rows)}条后续复核入表；其余未入表候选仍按原状态保留缺项，不能把这一批复核视为完成全部模糊项。", '']
|
||
return lines
|
||
|
||
|
||
def render():
|
||
cov = DATA['coverage']
|
||
companies = DATA['companies']
|
||
depth = sum(bool(c.get('profileOnly')) for c in companies)
|
||
origin = sum(bool(c.get('profileOnly')) or c.get('directoryOrigin') == 'yc-2025-2026' for c in companies)
|
||
promoted = origin - depth
|
||
reviewed = sum(bool(c.get('profileOnly')) and '人工复核' in c.get('classificationBasis', '') for c in companies)
|
||
years = Counter(c['year'] for c in companies)
|
||
income = Counter(c['revenueStatus'] for c in companies)
|
||
technical = Counter(c.get('technicalReview', {}).get('level', 'unreviewed') for c in companies)
|
||
assert cov['profilesRead'] + cov['failedProfiles'] == cov['candidateRecords']
|
||
assert cov['matchingProfiles'] == cov['existingProfiles'] + cov['newProfiles']
|
||
assert cov['matchingProfiles'] + cov['otherOrMissingYear'] + cov['unclearAI'] + cov['dateConflicts'] == cov['profilesRead']
|
||
assert origin == cov['newProfiles']
|
||
assert AUDIT['accessedAt'] == cov['accessedAt']
|
||
assert AUDIT['counts'] == cov
|
||
assert len(AUDIT['records']) == cov['profilesRead']
|
||
assert Counter(x['status'] for x in AUDIT['records']) == {
|
||
'imported': cov['newProfiles'], 'existing': cov['existingProfiles'],
|
||
'year-outside-or-missing': cov['otherOrMissingYear'],
|
||
'ai-unclear': cov['unclearAI'], 'date-conflict': cov['dateConflicts']}
|
||
assert len({x['ycId'] for x in AUDIT['records']}) == len(AUDIT['records'])
|
||
excluded_years = Counter(x['foundedYear'] for x in AUDIT['records'] if x['status'] == 'year-outside-or-missing')
|
||
outside_years = {year: count for year, count in excluded_years.items() if year is not None}
|
||
assert all(year not in (2025, 2026) for year in outside_years)
|
||
assert sum(outside_years.values()) + excluded_years[None] == cov['otherOrMissingYear']
|
||
year_detail = '、'.join(f'{year}年{count}项' for year, count in sorted(outside_years.items()))
|
||
lines = ['# AI 公司资料覆盖与缺项', '',
|
||
f"截至 {DATA['asOf']}，研究表含{len(companies):,}条公司或产品记录。YC候选池有逐条读取审计；其他来源为定向补充。清单尚不能作为全球AI公司普查，也不能将收入未知解释为零。", '',
|
||
'验收范围已于2026-10-30确认为：以确认的公开来源清单为边界，逐条核对并标明缺项。下方区分已逐条审计的候选池与定向补充来源；已使用某来源不代表该来源已被完整覆盖。', '',
|
||
f"[分类和数据工作台]({BASE})链接原始证据，[收入样本快照](/docs/other-research/ai-company-research/income-snapshot)展示当前可计算的MRR样本。", '',
|
||
'## 候选池与公司表的关系', '',
|
||
'| 环节 | 记录数 | 含义 |', '| --- | --- | --- |',
|
||
f"| YC批次候选 | {cov['candidateRecords']:,} | 从公开镜像发现，随后读取YC官方页面 |",
|
||
f"| 官方页面读取 | {cov['profilesRead']:,} | 此候选池读取失败{cov['failedProfiles']}条 |",
|
||
f"| 初筛匹配 | {cov['matchingProfiles']:,} | 成立年及AI相关描述通过初筛，尚非逐家商业验证 |",
|
||
f"| 与原表重合 | {cov['existingProfiles']} | URL匹配，未再次新增 |",
|
||
f"| 新增目录记录 | {cov['newProfiles']:,} | 原始入表来源，后续深化不改变发现计数 |",
|
||
f"| 原目录列为范围外年份 | {sum(outside_years.values())} | {year_detail}；原快照自述，不是独立登记核验 |",
|
||
f"| 原目录未给成立年 | {excluded_years[None]} | 与已列范围外年份分开，仍待补证 |",
|
||
f"| AI业务待确认 | {cov['unclearAI']} | 不强行把背景关键词当主营 |",
|
||
f"| 成立年与批次冲突 | {cov['dateConflicts']} | 另保留核查记录 |", '',
|
||
f"全表由{depth}条目录基础项和{len(companies)-depth}条个案或平台记录组成。候选池已匹配项之外另有{len(companies)-cov['matchingProfiles']}条记录，包含其他来源及发布/转型对照；其中已有{promoted}条原目录记录深化为个案，仍保留目录来源。两种统计边界不同。候选池数字只是该镜像快照的覆盖，Bud等后续定向补充不回填为原候选池已覆盖。", '',
|
||
'## 成立年与证据深度', '',
|
||
'| 维度 | 当前记录 | 解读 |', '| --- | --- | --- |',
|
||
f"| 记录为2025年成立 | {years[2025]} | 成立来源和精度见公司明细 |",
|
||
f"| 记录为2026年成立 | {years[2026]} | 不将产品发布日期代替成立日 |",
|
||
f"| 成立年未知或范围外 | {sum(v for k,v in years.items() if k not in (2025,2026))} | 发布/转型对照单列，不进入两年成立分组 |",
|
||
f"| 目录业务分类人工复核 | {reviewed} | 仅复核主营分类，不代表技术或财务审计 |",
|
||
f"| 其他目录基础项 | {depth-reviewed} | 规则初分或资料不足，继续待复核 |",
|
||
f"| 有团队数字 | {sum(c['team'] is not None for c in companies)} | 多为自报Team Size或Employees，时点与口径不统一 |",
|
||
f"| 专项技术证据记录 | {len(companies)-technical['unreviewed']} | 其中{technical['description']}条自述、{technical['public-artifact']}条公开材料、{technical['independent-test']}条第三方评测 |",
|
||
f"| 企业披露收入线索 | {income['self']} | 含公司或交易当事方披露、历史、下界及币种不明，不等于可比ARR |",
|
||
f"| 仅平台收入线索 | {income['platform']} | 同时有企业披露者计入上一行，不重复计数 |",
|
||
f"| 仅第三方估算 | {income['estimate']} | 不与直接披露混合 |",
|
||
f"| 暂无可用收入数字 | {income['unknown']} | 包含尚未逐家搜索的目录项，不代表没有收入 |", '',
|
||
'## 业务分类与数据入口', '',
|
||
'| 业务类别 | 记录数 |', '| --- | --- |',
|
||
]
|
||
counts = Counter(c['cat'] for c in companies)
|
||
for category in DATA['categories']:
|
||
lines.append(f"| [{category['name']}]({BASE}?category={category['id']}) | {counts[category['id']]} |")
|
||
lines += ['', '## 已使用来源的分布', '',
|
||
f"{len(DATA['evidence']):,}条证据记录对应{len({e['url'] for e in DATA['evidence']}):,}个不同URL。不同URL不自动构成独立验证；同一声明可能由公司、投资方和媒体重复转述。", '',
|
||
'| 来源 | 证据记录 | 不同URL | 用途及限制 |', '| --- | --- | --- | --- |',
|
||
]
|
||
families = [('YC官方目录', 'www.ycombinator.com', '公司自述的成立、团队与业务；英文及加速器样本偏多'),
|
||
('TrustMRR', 'trustmrr.com', '支付平台重建指标及方法；公开者存在选择偏差，非财务审计'),
|
||
('a16z Speedrun', 'speedrun.a16z.com', '投资机构中的公司介绍及收入声明；存在利益关系'),
|
||
('TechCrunch', 'techcrunch.com', '原始采访或报道；转述公司数字不等于查账'),
|
||
('Sacra', 'sacra.com', '第三方估算；与直接披露分开')]
|
||
included = set()
|
||
for name, host, note in families:
|
||
entries = [e for e in DATA['evidence'] if urlsplit(e['url']).netloc == host]
|
||
included.add(host)
|
||
lines.append(f"| {name} | {len(entries)} | {len({e['url'] for e in entries})} | {note} |")
|
||
others = [e for e in DATA['evidence'] if urlsplit(e['url']).netloc not in included]
|
||
lines.append(f"| 其他官网、评测及公开资料 | {len(others)} | {len({e['url'] for e in others})} | 按每条来源限制理解，不能统一当作独立证据 |")
|
||
lines += uncertain_ai_followups()
|
||
lines += founding_year_followups()
|
||
lines += missing_year_followups()
|
||
lines += directory_rechecks()
|
||
lines += source_register()
|
||
lines += context_methods()
|
||
lines += candidate_register()
|
||
lines += ['', '## 尚未满足的研究条件', '',
|
||
'行业ARR比较仍缺统一业务截止日、币种、经常性定义和业务边界。现有平台MRR可描述已采集产品，不足以代表全部新公司。技术评测只覆盖所列版本与任务，不宜跨领域汇总为统一强弱分数。', '',
|
||
'下一轮优先补收入线索的日期及合同定义、成立年冲突、AI主营仍待核项、非YC和非英文来源，以及停止服务或被收购案例。这样能减少“只见赢家”和“只见融资公司”的偏差。公开来源池之外的未披露公司仍无法证明已被穷尽。', '',
|
||
]
|
||
return '\n'.join(lines)
|
||
|
||
|
||
def main():
|
||
parser = argparse.ArgumentParser(description=__doc__)
|
||
parser.add_argument('--check', action='store_true')
|
||
parser.add_argument('--document-export', type=Path)
|
||
args = parser.parse_args()
|
||
content = render()
|
||
if args.check:
|
||
if args.document_export is not None:
|
||
bundle = json.loads(args.document_export.read_text())
|
||
stored = next((d['content'] for d in bundle['documents'] if d['sourceSlug'] == SOURCE_SLUG), None)
|
||
if stored != content:
|
||
sys.exit('Research coverage report differs; review and regenerate')
|
||
print('Research coverage accounting verified; supplied document export compared when requested')
|
||
else:
|
||
TARGET.parent.mkdir(parents=True, exist_ok=True)
|
||
TARGET.write_text(content)
|
||
print(TARGET.relative_to(ROOT))
|
||
|
||
|
||
if __name__ == '__main__':
|
||
main()
|