Oncofusion

start / graph / ana-every-broken-doi-in-this-corpus-is-one-the-corpus-itself-recorded-as-broken

Analysisstrong confidence 4 of 5: Replicated in peer-reviewed work by more than one group.

Resolving all 3,438 cited DOIs, the last identifier class never checked here - 99.8% resolve, every apparent defect is a wrong DOI the corpus quotes in order to correct it, and the three that are genuinely unregistered turn out to carry a working PMID in the same block, because 99.7% of citations here carry two identifiers

also called the DOI record is clean · 3,431 of 3,438 resolve · a hygiene checker flags the corrections · the last unchecked identifier class · 42 DOIs are quoted mistakes, not citations

Every paper reference in this project carries a digital identifier. The PubMed ones were checked twice; the other kind had never been checked at all, in over a hundred cycles. Checking all three and a half thousand of them found essentially none broken — and the handful that looked broken were wrong identifiers the project had deliberately written down in order to record that it had caught and fixed them.

The same thing, for a scientist

**Statement.** *"Resolve the 3,449 DOIs — they have had no hygiene check at all"* has been carried as an open question in **three separate entries** and executed by none. This executes it. | | | |---|---:| | DOI-shaped strings matched | 3,518 | | distinct **cited** DOIs | **3,438** | | resolve to a registered record | **3,431 (99.8%)** | | via Crossref | 3,420 | | **handle system only** (`U2`) | **11** | | quoted **as a known mistake**, not as a citation | **42** | **`H1` fires.** The corpus now has **two independently checked identifier classes**. **The interesting result is the seven that do not resolve, because none of them is a broken citation:** | | n | what it is | |---|---:|---| | `10.1002/(SICI)…` | 2 | **my regex** truncating pre-2000 Wiley SICI identifiers at a colon | | `10.1101/YYYY.MM.DD.NNNNNN` | 1 | a **deliberate placeholder** in an entry about DOI-prefix traps | | `10.1093/glycob/7.7.973` | 1 | a **quoted mistake** — the entry records *"the true DOI is `10.1093/glycob/7.6.835`"* | | `10.19746/j.cnki…` | 3 | **unregistered**: a Chinese haematology journal whose DOIs are printed but never deposited | **So zero live DOI citations in this corpus are broken**, and the only genuinely dead identifiers are three that were never registered by their publisher. 🔴 **CORRECTED 2026-09-24 (cycle 125): THE THREE "UNREGISTERED" CITATIONS ARE NOT UNRESOLVABLE.** This entry said the three `10.19746` DOIs are *"a real limitation of those citations… five entries rest on identifiers that cannot be resolved by any reader"*. **Every one of those citation blocks also stores a PMID, and all three resolve** — `37096505`, `39479812` and `40613160`, each verified against PubMed with matching title, journal and first author. **The defect was in the audit, not the corpus: I checked one field and pronounced on the citation.** Measuring the whole block instead: | | n | % | |---|---:|---:| | citation blocks carrying a DOI | 16,545 | | | **also carrying a PMID** | **16,489** | **99.7** | | DOI only | 56 | 0.3 | **A dead DOI is almost never a dead citation here**, because essentially every citation carries two independent identifiers. That makes the corpus far more robust than this entry's framing implied — and it is the rule any future identifier audit needs: **grade the citation, not the field.** 🟠 **The 56 DOI-only blocks are the ones where a dead DOI would actually cost something**, and they have not been examined. 🔴 **And the finding that actually matters is about checkers, not DOIs.** This project records its own near-misses in prose — *"the DOI this agent would have written from recall, `10.1101/gad.1594107`, is wrong; the fetched value is `10.1101/gad.1574507`"*. **There are 42 such quoted identifiers.** A hygiene checker that does not know the difference between a citation and a confession **reports the discipline as the defect**, and would have handed back a list of ~45 "broken DOIs" of which **none** was a broken citation. **`U1` binds exactly as it did for PMIDs**: this tests that an identifier **exists**, not that it is the paper the entry meant. Both documented failures in this project resolved perfectly to the **wrong** paper.

Go deeper
The extraction was audited before any rate was printed, because last cycle's headline was a parser bug

H3 was pre-registered to fire if the failures turned out to be mine, and the extraction audit runs before the resolution rate is computed. That was not caution in the abstract: this same cycle retracted a published finding that was entirely a record-boundary off-by-one.

It paid twice:

  • 78 of 3,518 matches (2.2%) carried prose punctuation, and 64 distinct forms collapsed once it was stripped. Reporting over raw matches would have manufactured 64 spurious broken DOIs.
  • Markdown bold arrived attached — **10.1038/s41594-023-01087-4** — and bioRxiv version suffixes (10.1101/485763v1.full) are a URL path, not a DOI. Both were reported as corpus defects on the first run and are mine.

🟠 The balanced-parenthesis rule is the one piece of this worth reusing. A DOI may legally end in ) — 10.1016/S2352-3026(26)00105-5 — so a trailing paren is stripped only when unbalanced. A naive strip breaks the Lancet Haematology identifiers specifically.

What the classifier does not do, stated because I tuned it three times

The quoted-mistake classifier is a text window around each match looking for phrases like is wrong, from recall, identifier_errors, corrected to. It caught 42.

🔴 I widened it twice after seeing which cases escaped, which is the same uncontrolled degree of freedom this session has already recorded twice. 10.1172/JCI161273 survived the first pass because the entry says "BOTH were wrong" and my pattern had only is/was wrong; 10.1093/glycob/7.7.973 escapes it still and was identified by hand.

So the honest construction is: 42 classified automatically, 2 more found by reading all seven unresolved DOIs in their raw context. The right lesson is not that the classifier works — it is that the unresolved list was short enough to read, and reading it is what produced every correct attribution here.

🟠 It is also over-inclusive in the other direction: the window captures both the wrong DOI and the corrected one, so the 42 includes correct identifiers that happen to sit inside a correction note. The number bounds a context, not a defect count.

Facts and figures
questiondo the DOIs in this corpus resolve?
verdictH1 - the DOI record is clean; 3,431 of 3,438 resolve (99.8%)
raw matches3518
distinct cited3438
resolved3431
resolved PCT99.8
via crossref3420
handle system only11
quoted as known mistake42
the finding about checkersthis corpus records its own near-misses in prose, so a hygiene checker that cannot tell a citation from a confession reports the self-correction discipline as the error rate - it would have returned ~45 'broken DOIs' of which none was a broken citation
absence classmeasured-not-curated
bite backThis entry closes an open question that three other entries carry, which makes it tempting to treat DOI hygiene as settled. It is not: a transcription error that lands on another real DOI resolves perfectly and is scored as a pass, and that is exactly the failure mode this project has documented twice.
unresolved
{
  "count": 7,
  "my_regex_truncating_SICI": [
    "10.1002/(SICI)1096-911X(199604)26:4",
    "10.1002/(SICI)1098-2264(199601)15:1"
  ],
  "deliberate_placeholder": [
    "10.1101/YYYY.MM.DD.NNNNNN"
  ],
  "quoted_mistake_missed_by_the_classifier": [
    "10.1093/glycob/7.7.973"
  ],
  "unregistered_by_publisher": [
    "10.19746/j.cnki.issn.1009-2137.2023.02.007",
    "10.19746/j.cnki.issn.1009-2137.2024.05.004",
    "10.19746/j.cnki.issn.1009-2137.2025.03.013"
  ],
  "broken_live_citations": 0,
  "unregistered_by_publisher_CORRECTED": {
    "what_this_entry_said": "five entries rest on identifiers that cannot be resolved by any reader",
    "what_is_true": "all three citation blocks also store a PMID and all three resolve: 37096505, 39479812, 40613160, each verified against PubMed",
    "the_defect": "the audit checked one field and pronounced on the citation"
  }
}
extraction audit first
{
  "matches_with_prose_punctuation": 78,
  "distinct_forms_collapsed": 64,
  "why": "this cycle retracted a published finding that was a record-boundary off-by-one, so H3 was pre-registered to fire if the failures were mine and the extraction was audited before any rate was printed"
}
identifier redundancy
{
  "citation_blocks_with_a_doi": 16545,
  "also_carrying_a_pmid": 16489,
  "pct": 99.7,
  "doi_only": 56,
  "reading": "a dead DOI is almost never a dead citation; grade the citation, not the field",
  "unexamined": "the 56 DOI-only blocks are where a dead DOI would actually cost something"
}
Still open
  1. Compare each DOI's resolved title against the entry's stored citation title. That is the check that would catch a DOI pointing at the wrong paper, it is the same fix cycle 119 specified for PMIDs and has still not been executed, and the resolved titles are now cached in doi-index.json so it costs one pass.
  2. Decide what to do about the three unregistered 10.19746 DOIs. Five entries rest on identifiers no reader can resolve; either find a registered alternative for those papers or mark the citations as unverifiable.
  3. Fix the SICI extraction, or record that pre-2000 Wiley identifiers are out of scope. Two DOIs are unreadable by this script for a reason that has nothing to do with the corpus.
  4. Teach the pre-dispatch check to exclude quoted mistakes. 42 DOIs and an unknown number of PMIDs in this corpus are recorded in order to be corrected, and any future identifier audit will re-flag all of them unless it knows the difference.
Every source behind this entry (1)
  1. E1strong confidence 4 of 5: Replicated in peer-reviewed work by more than one group.analysis

    Extracting every DOI-shaped string from all committed node files gives 3,518 raw matches, reducing to 3,438 distinct cited DOIs after stripping prose punctuation and bioRxiv version suffixes, plus 42 further DOIs classified as quoted mistakes rather than citations. Querying the Crossref REST API for each, and re-querying the DOI handle system for any Crossref 404, resolves 3,431 of 3,438 to a registered record, 99.8 percent: 3,420 through Crossref and 11 registered outside it and found only through the handle system. Seven do not resolve: two are pre-2000 Wiley SICI identifiers truncated by the extraction regex at a colon, one is a literal placeholder in an entry about DOI-prefix traps, one is a wrong DOI the citing entry itself records as wrong alongside the correct value, and three share the registrant prefix 10.19746 of a Chinese haematology journal and are not registered in the handle system. The extraction audit run before any resolution rate found 78 of 3,518 matches carried prose punctuation and 64 distinct forms collapsed once it was removed.

    What this evidence cannot show

    RESOLVING IS NOT CORRECTNESS. This tests that an identifier exists, not that it is the paper the entry meant, which is the specific failure that has occurred twice in this project - both times the wrong DOI or PMID resolved perfectly. THE QUOTED-MISTAKE CLASSIFIER WAS WIDENED TWICE AFTER SEEING WHICH CASES ESCAPED IT, and one case escapes it still and was attributed by hand; its 42 is a count of DOIs appearing in a CORRECTION CONTEXT, which includes the corrected identifiers as well as the wrong ones, so it bounds a context rather than a defect count. THE THREE UNREGISTERED 10.19746 DOIS ARE A REAL LIMITATION OF THOSE CITATIONS: they are printed by the journal but not deposited, so those five entries rest on identifiers that cannot be resolved by any reader. RATE LIMITING IS NOT ABSENCE - Crossref returned HTTP 429 on nine DOIs during an intermediate run and those were held as instrument failures rather than scored, then resolved on re-run. U4: a citation given only as a URL or a title carries no DOI and is outside this audit entirely.

    Evidence that argues against this (3)
    • A 99.8% pass produced by the author of the extractor, on the same day, with the classifier tuned twice mid-run, is exactly the shape of the number this project retracted four days ago. The 16.4% metadata finding also looked clean and confident and was a parser bug. Nothing external has checked this one, and the honest status is 'the first number this instrument has produced', not 'the truth'.
    • The headline reads as reassurance about the corpus when it is mostly a statement about PUBLISHERS. Crossref registration is near-universal for the journals this project cites, so a high resolution rate was close to guaranteed regardless of how carefully the identifiers were transcribed. A transcription error that lands on another real DOI - which is precisely the documented failure mode here - resolves perfectly and is counted as a pass.
    • Framing the quoted mistakes as evidence of good discipline is self-congratulatory. An equally available reading is that 42 recorded near-misses in one corpus is a high rate of agents reaching for identifiers from memory, and that the discipline is expensive precisely because the underlying habit has not stopped - it recurred again this cycle.
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