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Record W3098572759 · doi:10.1136/ijgc-2020-igcs.4

4 Refining pathologic interpretation of endometrial carcinomas: lessons learned from a nationwide study in a new era of molecular classification

2020· article· en· W3098572759 on OpenAlexaff
Emily F. Thompson, Jutta Huvila, Samuel Leung, Julie Irving, Nicholas van der Westhuizen, Mary Kinloch, Alice Lytwyn, Monalisa Sur, Carlos Parra‐Herran, Amber Yasmeen, F. Gougeon, C Morin, Katherine Grondin, Saul Offman, Taylor Salisbury, E He, Julia M. Lawson, Jamie Vanden Broek, Cliff Bell, Kaoutar Ennour‐Idrissi, Christoph Wohlmuth, Danielle Vicus, Walter H. Gotlieb, Limor Helpman, Amy Lum, Janine Senz, D. Huntsman, B. Gilks, J.N. McAlpine

Bibliographic record

VenueInternational Journal of Gynecological Cancer · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsJuravinski Cancer CentreQueen Elizabeth II Health Sciences CentreDalhousie UniversityUniversité LavalHôtel-Dieu de QuébecCentre hospitalier universitaire de QuébecMcGill UniversitySunnybrook Health Science CentreCentre for Advancing Health OutcomesJewish General HospitalUniversity Health NetworkHealth Sciences CentreMcMaster UniversityUniversité de MontréalUniversity of SaskatchewanVancouver General HospitalRoyal Jubilee HospitalUniversity of British Columbia
Fundersnot available
KeywordsImmunohistochemistryContext (archaeology)MedicineMLH1OncologyInternal medicineStage (stratigraphy)PathologyCarcinomaDNA mismatch repairCancerBiologyColorectal cancer

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.055
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.053
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.096
GPT teacher head0.383
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2020
Admission routes1
Has abstractno

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