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Record W2149989622 · doi:10.1200/jco.2014.59.3160

<i>PIK3CA</i> Genotype and Treatment Decisions in Human Epidermal Growth Factor Receptor 2–Positive Breast Cancer

2015· letter· en· W2149989622 on OpenAlexaff
David W. Cescon, Philippe L. Bédard

Bibliographic record

VenueJournal of Clinical Oncology · 2015
Typeletter
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineGenotypingPersonalized medicineBreast cancerExome sequencingPrecision medicineMultiplexGenotypeExomeEpidermal growth factor receptorHuman Epidermal Growth Factor Receptor 2OncologyBioinformaticsInternal medicineCancerMutationGeneticsGenePathologyBiology

Abstract

fetched live from OpenAlex

Genotyping of patient tumors has been rapidly incorporated into both clinical trials and clinical practice over the last several years, with the goal of advancing personalized or precision cancer medicine. The crux of these efforts is to identify actionable alterations— genetic changes that can be used to guide individualized treatment. Dramatic advances in sequencing technologies and DNA isolation methods now enable multiplex hotspot mutation testing or targeted exome se

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.642
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.004
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 head0.139
GPT teacher head0.468
Teacher spread0.330 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations15
Published2015
Admission routes1
Has abstractyes

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