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Record W2156118488 · doi:10.3747/co.v17i3.610

Eastern Canadian Colorectal Cancer Consensus Conference: Setting the Limits of Resectable Disease

2010· article· en· W2156118488 on OpenAlexaffvenueabout
Michael M. Vickers, Benoît Samson, Bruce Colwell, C. Cripps, D. Jalink, S. El-Sayed, E. Chen, Geoff Porter, Rakesh Goel, James Villeneuve, Sudhir Sundaresan, Jamil Asselah, James Biagi, Derek J. Jonker, Laura A. Dawson, R. Létourneau, M. Rother, Jean A. Maroun, Michael P. Thirlwell, Mohamed K. Hussein, Mustapha Tehfé, Nancy Perrin, Neil R. Michaud, Nazik Hammad, P. Champion, R. Rajan, Ronald L. Burkes, Stéphane Barrette, Stephen Welch, Nirit Yarom, Timothy R. Asmis

Bibliographic record

VenueCurrent Oncology · 2010
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsCentre Hospitalier de l’Université de MontréalHôpital Notre-DameUniversity of TorontoHôpital Charles-Le MoyneCentre Hospitalier Universitaire de SherbrookeUniversity of OttawaMcGill University Health CentreCegep de Sept IlesPrincess Margaret Cancer CentreOttawa HospitalQueen's UniversityCredit Valley HospitalCape Breton Regional HospitalMontreal General Hospital
Fundersnot available
KeywordsMedicineColorectal cancerCancerDiseaseFamily medicineStatement (logic)Internal medicineOncology

Abstract

fetched live from OpenAlex

The annual Eastern Canadian Colorectal Cancer Consensus Conference was held in Montreal, Quebec, October 22-24, 2009. Health care professionals involved in the care of patients with colorectal cancer participated in presentation and discussion sessions for the purposes of developing the recommendations presented here. This consensus statement addresses current issues in the management colorectal cancer, such as the management of hepatic and pulmonary metastases, the role of monoclonal antibodies to the epidermal growth factor receptor, and the benefits and safety of chemotherapy in elderly patients. The management of gastrointestinal neuroendocrine tumours and gastric cancer are also discussed.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.992

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)0.0010.000

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 head0.099
GPT teacher head0.398
Teacher spread0.299 · 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 designObservational
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

Citations22
Published2010
Admission routes3
Has abstractyes

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