MétaCan
Menu
Back to cohort
Record W4408329120 · doi:10.1245/s10434-025-17132-z

ASO Visual Abstract: The Composite Endpoint of Liver Surgery CELS—Development and Validation of a Clinically Relevant Endpoint Requiring Lower Sample Size

2025· article· en· W4408329120 on OpenAlexaff
Jun Kawashima, Miho Akabane, Yutaka Endo, Selamawit Woldesenbet, Mujtaba Khalil, Kota Sahara, Andrea Ruzzenente, Luca Aldrighetti, Todd W. Bauer, Hugo P. Marques, Rita de Cássia Sobreira Lopes, Sara Oliveira, Guillaume Martel, Irinel Popescu, Matthew J. Weiss, Minoru Kitago, George A. Poultsides, Kazunari Sasaki, Shishir K. Maithel, Tom Hugh, Ana Gleisner, Federico Aucejo, Carlo Pulitanò, Feng Shen, François Cauchy, Bas Groot Koerkamp, Itaru Endo, Timothy M. Pawlik

Bibliographic record

VenueAnnals of Surgical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineSurgical oncologyClinical endpointSample (material)SurgeryRandomized controlled trialChromatography

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)0.026
metaresearch head score (Gemma)0.092
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.081
Threshold uncertainty score0.271

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.092
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0050.001
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0810.016

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 head0.173
GPT teacher head0.372
Teacher spread0.199 · 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 designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractno

Explore more

Same venueAnnals of Surgical OncologySame topicHepatocellular Carcinoma Treatment and PrognosisFrench-language works237,207