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Record W3135561905 · doi:10.21203/rs.3.rs-236645/v1

High p16 expression and heterozygous RB1 loss are biomarkers for CDK4/6 inhibitor resistance in ER+ breast cancer

2021· preprint· en· W3135561905 on OpenAlexaff
Marta Palafox, Laia Monserrat, Meritxell Bellet, Guillermo Villacampa, Abel González-Pérez, Mafalda Oliveira, Fara Brasó‐Maristany, Nusaïbah Ibrahimi, Srinivasaraghavan Kannan, Leonardo Mina, María Teresa Herrera-Abreu, Andreu Òdena, Mònica Sánchez-Guixé, Marta Capelán, Analía Azaro, Alejandra Bruna, Olga Rodríguez, Marta Guzmán, Judit Grueso, Cristina Viaplana, Javier Hernández‐Losa, Faye Su, Kui Lin, Robert B. Clarke, Carlos Caldas, Joaquı́n Arribas, Stefan Michiels, Alicia García‐Sanz, Nicholas C. Turner, Aleix Prat, Paolo Nucíforo, R. Dienstmann, Chandra Verma, Núria López-Bigas, Maurizio Scaltriti, Mónica Arnedos, Cristina Saura, Violeta Serra

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsInstitute of Cancer Research
FundersCongressionally Directed Medical Research ProgramsManchester Biomedical Research CentreNational Institutes of HealthFundació la Marató de TV3Fundación FeroIpsenInstituto de Salud Carlos IIIFundació Institut de Recerca Hospital Universitari Vall d’HebronGeneralitat de CatalunyaFundación Científica Asociación Española Contra el CáncerNational Institute for Health and Care ResearchHorizon 2020 Framework ProgrammeCancer Research UKAgència de Gestió d'Ajuts Universitaris i de RecercaPfizerNovartis Pharmaceuticals CorporationInstitute for Research in BiomedicineCentres de Recerca de CatalunyaGenentechMinisterio de Economía y CompetitividadMemorial Sloan-Kettering Cancer CenterEuropean CommissionBreast Cancer Research FoundationEli Lilly and Company
KeywordsCancer researchBreast cancerCancerOncologyExpression (computer science)Internal medicineMedicineComputer science

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.390
Teacher spread0.350 · 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

Citations12
Published2021
Admission routes1
Has abstractno

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