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Record W2145633869 · doi:10.1517/14728222.10.5.777

Novel targets in prostate cancer

2006· article· en· W2145633869 on OpenAlexaff
Dominik Berthold, Malcolm J. Moore

Bibliographic record

VenueExpert Opinion on Therapeutic Targets · 2006
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsProstate cancerMedicineContext (archaeology)SorafenibProstateCancerDiseaseOncologyInternal medicineCancer researchBioinformaticsBiology

Abstract

fetched live from OpenAlex

Despite recent advances in the understanding of the cellular and molecular biology of prostate cancer, new options for the treatment of prostate cancer remain elusive. Targeted therapies have shown promising activities in many solid tumours and the growing number of targets and targeted agents is creating numerous opportunities for clinical research in advanced prostate cancer. At ASCO 2006 in Atlanta, a clinical science symposium on novel targets in prostate cancer was presented. It consisted of three abstracts, each of which was followed by a discussant who reviewed the work and placed it in the overall context of current approaches to treating prostate cancer. The three abstracts were a discussion of a new method for quantification of the androgen receptor; the impact of high-dose vitamin D plus chemotherapy on hormone refractory disease and on the risk of thromboembolic disease; and the paradoxical effects seen with the raf-kinase and vascular endothelial growth factor inhibitor sorafenib, which produced improvement in bone scans in the absence of any prostate-specific antigen responses.

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: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.041
GPT teacher head0.359
Teacher spread0.318 · 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
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

Citations5
Published2006
Admission routes1
Has abstractyes

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