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The Effect of Level I Evidence on Surgical Decision Making in the United States Versus Canada

2018· article· en· W2909859417 on OpenAlexaffabout
Andrew Jawa, Jason L. Pittman, Michael P. Carducci, Scott Koenig, Mohit Bhandari, Paul Tornetta

Bibliographic record

VenueJAAOS Global Research and Reviews · 2018
Typearticle
Languageen
FieldMedicine
TopicShoulder and Clavicle Injuries
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: In this study, we examined the difference that randomized trials favoring either surgery or nonsurgical treatment had on the surgical indications of American versus Canadian surgeons. METHODS: One randomized trial favoring surgical management of clavicle fractures and another one favoring nonsurgical management of Achilles tendon ruptures were used. American and Canadian orthopaedic surgeons were surveyed regarding their surgical indications for these injuries. RESULTS: More than 2000 US and 200 Canadian responses were received. For clavicles, 57% of US respondents indicated that the trial changed their practice, with 64% operating on more fractures, compared with Canadians at 78% and 68%, respectively. For Achilles, 37% of US respondents indicated that the trial changed their practice, with 29% operating on fewer ruptures, compared with Canadians at 72% and 67%, respectively. CONCLUSION: American surgeons seem more willing to alter their practice to "evidence-based" indications for a trial that favors surgery rather than one that does not.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.213
GPT teacher head0.560
Teacher spread0.347 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2018
Admission routes2
Has abstractyes

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