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Record W2083895996 · doi:10.3747/co.v18i3.857

Canadian Initiatives for Locally Advanced Breast Cancer Research and Treatment: Inaugural Meeting of the Canadian Consortium for LABC

2011· article· en· W2083895996 on OpenAlexaffvenueabout
Muriel Brackstone, A. Robidoux, Stephen Chia, J. Mackey, Rebecca Dent, Jean-François Boileau, Mark Clemons

Bibliographic record

VenueCurrent Oncology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsUniversity of OttawaSunnybrook Health Science CentreUniversity of AlbertaUniversité de MontréalOttawa HospitalBC Cancer AgencyLondon Health Sciences Centre
Fundersnot available
KeywordsBreast cancerMedicineTranslational researchPresentation (obstetrics)Translational scienceClinical trialMedical physicsMedical educationCancerPathologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

The inaugural Canadian Consortium for LABC (locally advanced breast cancer) conference was held at Langdon Hall, Cambridge, Ontario, April 11–12, 2010. The meeting focused on current and future directions in labc treatment and research, the specific benefits of labc as a model for clinical and translational research, strategies for increased national and international collaboration, and ongoing clinical trials. Exciting Canadian initiatives in labc research are underway, focusing on identifying molecular signatures that will allow for the development of new tailored therapies. The challenge of identifying patient subgroups for accrual is being addressed through strategies to foster and improve national collaboration. This meeting report includes highlights from each presentation at the conference.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.672

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0080.003
Scholarly communication0.0050.001
Open science0.0020.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0120.002

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 head0.128
GPT teacher head0.411
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2011
Admission routes3
Has abstractyes

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