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Record W4402831100 · doi:10.1097/corr.0000000000003239

On Patient Safety: Could Surgical Fads Have Something in Common With the World’s Most Famous Secret Agent?

2024· article· en· W4402831100 on OpenAlexaff
Kari Kanto, Clare L. Ardern, Jonathan W. Scott, Simo Taimela, Trevor Corson, Teppo L. N. Järvinen

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineSurgeryGeneral surgery

Abstract

fetched live from OpenAlex

From the Column Editor: The goal of the "On Patient Safety" column is to explore the relationship between patient safety and clinical efficacy.In this month's guest column, the head of the Finnish Center for Evidence-Based Orthopedics (FICEBO), Teppo L. N. Järvinen MD, PhD, gets to the heart of that relationship by using Scott's parabola to illuminate the underlying credulity of our profession.I found his analysis-along with our continued embrace of "half parabolas"-to be highly important and germane in today's practice environment, and I hope you will, too.

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)0.018
metaresearch head score (Gemma)0.080
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.080
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.016
Scholarly communication0.0130.019
Open science0.0020.006
Research integrity0.0140.017
Insufficient payload (model declined to judge)0.0290.004

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 head0.598
GPT teacher head0.625
Teacher spread0.027 · 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
GenreCommentary

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
Published2024
Admission routes1
Has abstractno

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