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Record W2565591403 · doi:10.3747/co.23.3384

Report from the 17th Annual Western Canadian Gastrointestinal Cancer Consensus Conference; Edmonton, Alberta; 11–12 September 2015

2016· article· en· W2565591403 on OpenAlexafffundvenueabout
Karen Mulder, Shimaa Ahmed, J. D. Davies, Corinne Doll, Scot Dowden, Sharlene Gill, Vinessa Gordon, Pamela Hebbard, Howard J. Lim, Andrew McFadden, John Paul McGhie, Jungeun Park, Rebecca Wong

Bibliographic record

VenueCurrent Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsUniversity of British ColumbiaUniversity of ManitobaBC Cancer AgencyCancerCare ManitobaSaskatchewan Cancer AgencyUniversity of AlbertaUniversity of SaskatchewanAlberta Cancer FoundationUniversity of Calgary
FundersLEO PharmaCelgeneAmgen CanadaAmgenSirtex MedicalEli Lilly and CompanyF. Hoffmann-La Roche
KeywordsMedicineMultidisciplinary approachPresentation (obstetrics)Family medicineHealth professionalsHealth careStatement (logic)Gastrointestinal cancerCancerColorectal cancerSurgeryPolitical scienceInternal medicine

Abstract

fetched live from OpenAlex

The 17th annual Western Canadian Gastrointestinal Cancer Consensus Conference (wcgccc) was held in Edmonton, Alberta, 11-12 September 2015. The wcgccc is an interactive multidisciplinary conference attended by health care professionals from across Western Canada (British Columbia, Alberta, Saskatchewan, and Manitoba) who are involved in the care of patients with gastrointestinal cancer. Surgical, medical, and radiation oncologists; pathologists; radiologists; and allied health care professionals participated in presentation and discussion sessions for the purposes of developing the recommendations presented here. This consensus statement addresses current issues in the management of gastric 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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.999

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)0.0020.000

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 head0.086
GPT teacher head0.384
Teacher spread0.298 · 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 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

Citations4
Published2016
Admission routes4
Has abstractyes

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