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Record W2465406332 · doi:10.1097/ppo.0000000000000199

Molecular Triage Trials in Colorectal Cancer

2016· review· en· W2465406332 on OpenAlexaff
Mark H. O’Hara, Stanley R. Hamilton, Peter J. O’Dwyer

Bibliographic record

VenueThe Cancer Journal · 2016
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsSt. Peter's Hospital
Fundersnot available
KeywordsColorectal cancerMedicineClinical trialOncologyDiseaseCancerTriageTargeted therapyClinical study designInternal medicineBioinformaticsIntensive care medicineBiologyMedical emergency

Abstract

fetched live from OpenAlex

Advances in the understanding of genomic alterations in cancer, and the various therapies targeted to these alterations have permitted the design of trials directed to bringing this science to the clinic, with the ultimate goal of tailoring therapy to the individual. There is a high need for advances in targeted therapy in colorectal cancer, a disease in which only 2 classes of targeted therapies are approved for use in colorectal cancer, despite the majority of colorectal cancers containing a potentially targetable mutation. Here we outline the key elements to the design of these clinical trials and summarize the current active molecular triage trials in colorectal cancer.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.123
GPT teacher head0.455
Teacher spread0.332 · 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 designOther design
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

Citations1
Published2016
Admission routes1
Has abstractyes

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