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Record W4285411946 · doi:10.20517/ais.2022.17

Erratum: White paper: definitions of artificial intelligence and autonomous actions in clinical surgery

2022· erratum· en· W4285411946 on OpenAlexaff
Andrew A. Gumbs, F. Alexander, Konrad Karcz, Élie Chouillard, Roland S. Croner, Jasamine Coles‐Black, Belinda De Simone, Michel Gagner, Brice Gayet, Vincent Grasso, Alfredo Illanes, Takeaki Ishizawa, Luca Milone, Mehmet Mahir Özmen, Micaela Piccoli, Stefanie Spiedel, Gaya Spolverato, Patricia Sylla, Mohammad Abu Hilal, Lee L. Swanström

Bibliographic record

VenueArtificial Intelligence Surgery · 2022
Typeerratum
Languageen
FieldMedicine
TopicArtificial Intelligence in Healthcare and Education
Canadian institutionsHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsWhite (mutation)Computer scienceWhite paperArtificial intelligenceCognitive scienceMedicinePsychologyHistoryBiology

Abstract

fetched live from OpenAlex

No

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 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)0.008
metaresearch head score (Gemma)0.065
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.065
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0060.005
Scholarly communication0.0070.006
Open science0.0040.003
Research integrity0.0190.022
Insufficient payload (model declined to judge)0.0240.018

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 head0.410
GPT teacher head0.438
Teacher spread0.028 · 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
GenreEditorial

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
Published2022
Admission routes1
Has abstractyes

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