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Record W7073708710

Recommendations for improved acute pain services: Canadian collaborative acute pain initiative.

2004· article· en· W7073708710 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship (California Digital Library) · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsnot available
Fundersnot available
KeywordsAcute painMultidisciplinary approachPain managementAcute careAcute hospitalMEDLINEOutcome (game theory)EpidemiologyAcute stroke
DOInot available

Abstract

fetched live from OpenAlex

The Canadian Collaborative Acute Pain Initiative, established in 2002, is a voluntary, multidisciplinary consortium of acute pain health professionals from across Canada whose goal is to improve acute pain management through discussion and consensus. The group met in January 2002 to define strategic areas related to the treatment of acute pain. The areas identified were: the definition of pain; the epidemiology of pain; the concept of an 'ideal' acute pain management service; education; therapeutic options; symptom management; and research and safety. In November 2002, a second meeting was held to develop objectives and recommendations for the management of acute pain based on the defined areas. The outcome of these discussions is summarized in this paper.

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)0.031
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: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.007
Science and technology studies0.0060.002
Scholarly communication0.0050.004
Open science0.0060.004
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0440.012

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 head0.012
GPT teacher head0.206
Teacher spread0.194 · 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
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
Published2004
Admission routes1
Has abstractyes

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