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Record W2001823700 · doi:10.1517/14728210903142147

Emerging drugs for prostate cancer

2009· review· en· W2001823700 on OpenAlexaff
Kashif Siddiqui, Laurence Klotz

Bibliographic record

VenueExpert Opinion on Emerging Drugs · 2009
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineProstate cancerAngiogenesisAndrogen receptorPharmacologyMatrix metalloproteinase inhibitorTyrosine kinaseCancerCancer researchMatrix metalloproteinaseInternal medicineReceptor

Abstract

fetched live from OpenAlex

Prostate cancer mortality usually occurs as a result of castrate resistant disease. Many approaches are currently being evaluated to improve the treatment of this condition. These include drugs that induce androgen deprivation, that is, LHRH antagonists; more active or less toxic chemotherapy agents; immunologic approaches, including passive and active immunization; drugs that target the androgen receptor and/or androgen synthesis; drugs that target specific pathways, including tyrosine kinase inhibitors, angiogenesis inhibitors, endothelin antagonists and matrix metalloproteinase inhibitors; and antioxidants and cell cycle inhibitors. Many of these agents seem promising. The rationale, biologic activity and therapeutic results of these emerging drugs are reviewed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.932
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.446
Teacher spread0.380 · 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.

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

Citations8
Published2009
Admission routes1
Has abstractyes

Explore more

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