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Record W2144005610 · doi:10.1586/era.12.71

New frontiers in therapeutic resistance in cancer

2012· article· en· W2144005610 on OpenAlexaffabout
Andrea Sartore‐Bianchi, Mauro Delorenzi, Thérèse Gagnon-Kugler, Caroline Rousseau, Gerald Batist

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsMcGill UniversityUniversité LavalQuebec - Clinical Research Organization in CancerHôtel-Dieu de Québec
Fundersnot available
KeywordsMedicinePersonalized medicinePrecision medicineDilemmaResistance (ecology)Clinical trialBioinformaticsInternal medicinePathology

Abstract

fetched live from OpenAlex

Despite advances in personalized medicine and targeted therapies, therapeutic resistance remains a persistent dilemma encountered by clinicians, scientists and patients. In this article we summarize the highlights of the third Quebec Conference on Therapeutic Resistance in Cancer. This unique meeting provided researchers and clinicians with insights into: intrinsic and acquired resistance; tumor heterogeneity; complexities of biomarker-driven trials; challenges of 'omics data analysis; and models of clinical applications of personalized medicine. Emphasized throughout the conference was the importance of collaborations - between industry and academia, and between basic researchers and clinicians - so that therapeutic resistance can be studied where it matters most, in patients.

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 score0.790
Threshold uncertainty score0.547

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 head0.018
GPT teacher head0.329
Teacher spread0.311 · 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

Citations5
Published2012
Admission routes2
Has abstractyes

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