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Record W3089867246 · doi:10.1016/j.hpb.2020.09.013

Management of early hepatocellular carcinoma: results of the Delphi consensus process of the Americas Hepato-Pancreato-Biliary Association

2020· article· en· W3089867246 on OpenAlexaff
Sepideh Gholami, Lauren M. Perry, Jason W. Denbo, Kenneth D. Chavin, Philippa Newell, Quan P. Ly, Charles R. St. Hill, Gareth Morris‐Stiff, Jonathan Kessler, Timothy L. Frankel, Neehar D. Parikh, Prejesh Philips, George I. Salti, Toms Augustin, Federico Aucejo, Meelie DebRoy, Natalie G. Coburn, Susanne G. Warner

Bibliographic record

VenueHPB · 2020
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineHepatocellular carcinomaAssociation (psychology)DelphiDelphi methodGeneral surgeryInternal medicineGastroenterologyArtificial intelligence

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

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: aff_core · design weight: 5595.24 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: policy
about Canada: no
confidence: high

No abstract; Delphi consensus statement on clinical management of early hepatocellular carcinoma.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

The work concerns clinical management of early hepatocellular carcinoma.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: medium

Delphi consensus on clinical management of early HCC; method used for care guidance, clinical object (no abstract).

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)0.094
metaresearch head score (Gemma)0.086
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0940.086
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.047
GPT teacher head0.253
Teacher spread0.206 · 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
GenreOther

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

Citations6
Published2020
Admission routes1
Has abstractno

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