MétaCan
Menu
Back to cohort
Record W2901680053 · doi:10.1016/j.hpb.2018.09.022

Patient blood management for liver resection: consensus statements using Delphi methodology

2018· article· en· W2901680053 on OpenAlexaff
Julie Hallet, Shiva Jayaraman, Guillaume Martel, Jean‐François Ouellet, Yulia Lin, Stuart A. McCluskey, Kaitlyn Beyfuss, Paul J. Karanicolas, Kengo Asai, Jeffrey Barkun, K. Bertens, Prosanto Chaudhury, Sean P. Cleary, Michael Hogan, D. Jalink, Calvin Law, Scott Livingstone, I. McGilvray, Peter Metrakos, Mike Moser, Sulaiman Nanji, Jean‐François Ouellet, Pablo Serrano Balazote, John M. Shaw, Anton Skaro, Tsafrir Vanounou, Mark Walsh, Alice C. Wei, George Zogopoulos, Gareth Eeson, Simon Turcotte, Nikola Joly, Chris Wherett, Jordan Tarshis, Jeannie Callum, Susan Nahirniak

Bibliographic record

VenueHPB · 2018
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsUniversité LavalUniversity of OttawaUniversity Health NetworkUniversity of TorontoCentre hospitalier universitaire de QuébecOttawa HospitalSt Joseph's Health CentreHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineDelphi methodDelphiPerioperativePsychological interventionLikert scaleBlood managementBlood transfusionIntensive care medicineSurgeryNursing

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.158
metaresearch head score (Gemma)0.188
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.158
Threshold uncertainty score0.837

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1580.188
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0050.002
Scholarly communication0.0030.003
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.335
GPT teacher head0.389
Teacher spread0.054 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations14
Published2018
Admission routes1
Has abstractno

Explore more

Same venueHPBSame topicHepatocellular Carcinoma Treatment and PrognosisFrench-language works237,207