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Record W1966793303 · doi:10.1108/cgij-04-2012-0013

Best practices in emergency medicine: what we have to consider if we wish to get it right

2013· article· en· W1966793303 on OpenAlex
James Ducharme

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Governance An International Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsWishBest practiceComputer sciencePublic relationsInternet privacyBusinessPolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

Abstract Purpose The purpose of this paper is to define best practice, while identifying the impediments to its implementation. Design/methodology/approach The paper takes the form of a commentary. Findings There is as of yet no accepted definition of best practice that has both face and construct validity. Practical implications Defining what best practice means for health systems around the world will require a collaborative approach, adapting recommendations to local culture and resources. Avoiding a silo approach that could result in unintended consequences and conflicting recommendations can only be achieved with a patient-centric approach. Holistic patient care with consideration of varying societies' needs as a whole is the only way to truly offer best practice recommendations. Emergency medicine needs to be a leader in stepping away from the silo approach and establishing what truly is best in patient care. Originality/value Practical application of concepts of best practice will be difficult. Of necessity they will vary from country to country and from one level of care to another.

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.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.532
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.127
GPT teacher head0.480
Teacher spread0.354 · 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