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Record W3202492551 · doi:10.1016/j.bja.2021.08.023

Six Sigma in surgery: how to create a safer culture in the operating theatre using innovative technology

2021· editorial· en· W3202492551 on OpenAlexafffund
Anne Sophie H.M. van Dalen, Jeanett Strandbygaard, Isabelle Van Herzeele, Sylvain Boet, Teodor Grantcharov, Marlies P. Schijven

Bibliographic record

VenueBritish Journal of Anaesthesia · 2021
Typeeditorial
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsSt. Michael's HospitalOttawa Hospital
FundersTakeda CanadaIntuitive
KeywordsSAFERSix SigmaTask (project management)Process (computing)Patient safetyLean Six SigmaSafety cultureProcess managementComputer scienceHealth careEngineeringOperations managementSystems engineeringPolitical scienceOperating systemManagementComputer security

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)0.017
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.983
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.054
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0050.004
Science and technology studies0.0050.004
Scholarly communication0.0160.007
Open science0.0060.003
Research integrity0.0380.033
Insufficient payload (model declined to judge)0.0130.009

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 head0.040
GPT teacher head0.369
Teacher spread0.329 · 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.

Study designNot applicable
DomainMethods
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

Citations13
Published2021
Admission routes2
Has abstractno

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