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Record W2017958518 · doi:10.1097/igc.0000000000000289

Gynecologic Cancer InterGroup (GCIG) Consensus Review for Clear Cell Carcinoma of the Ovary

2014· review· en· W2017958518 on OpenAlexaff
Aikou Okamoto, Rosalind Glasspool, Seiji Mabuchi, Noriomi Matsumura, Hiroyuki Nomura, Hiroaki Itamochi, Masashi Takano, Tadao Takano, Nobuyuki Susumu, Daisuke Aoki, Ikuo Konishi, Alan Covens, Jonathan A. Ledermann, Delia Mezzazanica, Christopher Steer, David Millan, Iain A. McNeish, Jacobus Pfisterer, Sokbom Kang, Laurence Gladieff, Jane Bryce, Amit M. Oza

Bibliographic record

VenueInternational Journal of Gynecological Cancer · 2014
Typereview
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsPrincess Margaret Cancer CentreSunnybrook Hospital
FundersCancer Research UK
KeywordsMedicineCarboplatinSerous carcinomaOncologyOvaryClear cell carcinomaInternal medicineSerous fluidStage (stratigraphy)Ovarian cancerIrinotecanPI3K/AKT/mTOR pathwayPaclitaxelCisplatinChemotherapyGynecologic oncologyBRCA mutationClinical trialGynecologyCancerColorectal 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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.068
GPT teacher head0.403
Teacher spread0.334 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations175
Published2014
Admission routes1
Has abstractno

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