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Record W4319602588 · doi:10.21203/rs.3.rs-2488586/v1

Clinical testing of transcriptome-wide expression profiles in high-risk localized and metastatic prostate cancer starting androgen deprivation therapy: an ancillary study of the STAMPEDE abiraterone Phase 3 trial

2023· preprint· en· W4319602588 on OpenAlexaff
Gerhardt Attard, Marina Parry, Emily Grist, Larissa Mendes, Peter Dutey‐Magni, Ashwin Sachdeva, Chris Brawley, Laura Murphy, J. Proudfoot, Sharanpreet Lall, Yang Liu, Stefanie Friedrich, Mazlina Ismail, Alex Hoyle, Adnan Ali, Áine Haran, Anna Wingate, Leila Zakka, Daniel Wetterskog, Claire Amos, Nafisah B Atako, Victoria Wang, Hannah Rush, Robert J. Jones, Hing Y. Leung, William Cross, Silke Gillessen, Chris Parker, Simon Chowdhury, Tamara L. Lotan, Teresa Marafioti, Alfonso Urbanucci, Edward M. Schaeffer, Daniel E. Spratt, David Waugh, Thomas Powles, Daniel M. Berney, Matthew R. Sydes, Mahesh Parmar, Anis Hamid, Felix Y. Feng, Christopher J. Sweeney, Elai Davicioni, Noel W. Clarke, Nicholas D. James, Louise Brown

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsSt. Thomas Hospital
FundersDOD Prostate Cancer Research ProgramJohn Black Charitable FoundationVeracyteNational Institute for Health and Care ResearchPfizerAstellas PharmaClovis OncologyMedical Research CouncilSanofiProstate Cancer UKCancer Research UKProstate Cancer Foundation
KeywordsProstate cancerMedicineAndrogen deprivation therapyAbiraterone acetatePTENOncologyInternal medicineRadiation therapyAndrogen receptorTranscriptomeCancerContext (archaeology)MetastasisAndrogenBiochemical recurrenceClinical trialHormoneBiologyProstatectomyGene expressionPI3K/AKT/mTOR pathwayGene

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.283
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.262
GPT teacher head0.498
Teacher spread0.235 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractno

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