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Record W4390547860 · doi:10.1056/nejmc2313228

Enzalutamide in Biochemically Recurrent Prostate Cancer

2024· letter· en· W4390547860 on OpenAlexaff

Bibliographic record

VenueNew England Journal of Medicine · 2024
Typeletter
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineEnzalutamideProstate cancerCancerOncologyInternal medicineAndrogen receptor

Abstract

fetched live from OpenAlex

To the Editor: In the EMBARK trial, Freedland et al. (Oct. 19 issue) 1 provide evidence for the efficacy of androgen-receptor blockade by enzalutamide without concomitant medical castration in the treatment of biochemically recurrent prostate cancer. If this result could be shown to be generalizable to other stages of prostate cancer, it would eliminate the use of injectable drugs (which are widely used and expensive) to achieve medical castration. Effective hormonal therapy for prostate cancer could be achieved with oral agents alone, a major advance in the field. However, it would be helpful to know the effects of single-agent enzalutamide on . . .

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)0.001
metaresearch head score (Gemma)0.006
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 score0.019
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0190.012
Insufficient payload (model declined to judge)0.0060.003

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 head0.033
GPT teacher head0.349
Teacher spread0.317 · 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

Citations1
Published2024
Admission routes1
Has abstractno

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