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Record W4411842050 · doi:10.1080/14796694.2025.2475730

Enzalutamide treatment of patients with advanced prostate cancer across the disease spectrum: plain language review

2025· review· en· W4411842050 on OpenAlexaff
Paul Dato, Jose De La Cerda, Andrew J. Armstrong, Arun Azad, Ciara Conduit, Gabriel P. Haas, Kenneth Kernen, Zachary Klaassen, Raj Patel, Fred Saad, Neal D. Shore, Stephen J. Freedland, Lawrence I. Karsh

Bibliographic record

VenueFuture Oncology · 2025
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineEnzalutamideProstate cancerDiseaseOncologyCancerInternal medicineAndrogen receptor

Abstract

fetched live from OpenAlex

GOAL: To present data from published clinical trials of treatment of patients with prostate cancer with enzalutamide described in plain language and in a dashboard format available at: https://clinical-trials.dimensions.ai/enzalutamide-clinical-review/. RATIONALE: Treatments that are clinically active in advanced prostate cancer may benefit patients as they are treated earlier in the disease. OBJECTIVE: To show how overall survival improves as patients are treated with enzalutamide earlier in the disease.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.941
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.412
Teacher spread0.395 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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