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Record W4394824835 · doi:10.1016/s0140-6736(24)00747-5

The Lancet Breast Cancer Commission

2024· review· en· W4394824835 on OpenAlexfundno aff
Charlotte E. Coles, Helena Earl, Benjamin O. Anderson, Carlos H. Barrios, Maya Bienz, Judith M. Bliss, David Cameron, Fátima Cardoso, Wanda Cui, Prudence A. Francis, Reshma Jagsi, Felícia Marie Knaul, Stuart McIntosh, Kelly‐Anne Phillips, Lukas Radbruch, M Thompson, Fabrice André, Jean Abraham, Indrani Bhattacharya, Maria Alice Franzoi, Lynsey M Drewett, Alexander Fulton, Farasat Kazmi, Dharrnesha Inbah Rajah, Miriam Mutebi, Dianna Ng, Szeyi Ng, Olufunmilayo I. Olopade, William E. Rosa, Jeffrey Rubasingham, Dingle Spence, Hilary Stobart, Inês Vaz-Luís, Cynthia Villarreal‐Garza, Héctor Arreola‐Ornelas, Afsan Bhadelia, Judy C. Boughey, Sanjoy Chatterjee, David Dodwell, Svetlana V. Doubova, Dorothy Du Plooy, Beverley M. Essue, Neha Goel, Julie R. Gralow, Sarah T. Hawley, Belinda E. Kiely, Ritse M. Mann, Shirley Mertz, Carlo Palmieri, Philip Poortmans, Tanja Španić, Lesley Stephen, Fraser Symmans, Catherine Towns, Didier Verhoeven, Sarah Vinnicombe, David Watkins, Cheng Har Yip, Brian J. Zikmund‐Fisher

Bibliographic record

VenueThe Lancet · 2024
Typereview
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
FundersSchool of Medicine, Emory UniversityInstitut Gustave-RoussyInstitute of GeneticsQueen's UniversityNIH Clinical CenterPeter MacCallum Cancer CentreCambridge University HospitalsFundação ChampalimaudQueen's University BelfastUniversity of CambridgeBreast Cancer NowDepartment of Health and Social CareNational Institute for Health and Care ResearchAgence Nationale de la RechercheUniversity of MiamiUniversity of WashingtonEmory UniversityUniversity of MelbourneNIHR Cambridge Biomedical Research CentreWorld Health Organization
KeywordsCommissionBreast cancerMultidisciplinary approachMedicineEquity (law)European commissionCancerPolitical scienceFamily medicineBusinessLawInternal medicineEuropean union

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.065
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0650.041

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 head0.250
GPT teacher head0.461
Teacher spread0.210 · 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 designNot applicable
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

Citations154
Published2024
Admission routes1
Has abstractno

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