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Record W2949917654 · doi:10.21037/atm.2019.05.86

The PD-1/PD-L1 pathway in advanced prostate cancer—have we milked this cow?

2019· letter· en· W2949917654 on OpenAlexaff
Sarah Picardo, Aaron R. Hansen

Bibliographic record

VenueAnnals of Translational Medicine · 2019
Typeletter
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer Centre
Fundersnot available
KeywordsPembrolizumabProstate cancerMedicineImmunotherapyCancerOncologyPD-L1Lung cancerInternal medicineMelanomaCancer research

Abstract

fetched live from OpenAlex

We would like to thank Dr. Fay and Dr. Antonarakis for their insightful comments on immunotherapy (IO) in advanced prostate cancer and specifically their commentary on the recently published KEYNOTE-028 study on the use of pembrolizumab in programmed cell death protein-1 ligand (PD-L1) positive metastatic castrate resistant prostate cancer (mCRPC) (1). As described by the authors, monotherapy with checkpoint inhibitors has not demonstrated the dramatic response rates in mCRPC that were shown in other cancer types such as melanoma and non-small cell lung cancer (NSCLC).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.003
metaresearch head score (Gemma)0.017
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: Editorial · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0260.028
Insufficient payload (model declined to judge)0.0050.005

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 head0.057
GPT teacher head0.345
Teacher spread0.288 · 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
GenreEditorial

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

Citations9
Published2019
Admission routes1
Has abstractyes

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