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Record W6925473368 · doi:10.17605/osf.io/6em32

Evaluations of clinical practice guidelines, protocols, and pathways used in rural and remote Australia, Canada, and Aotearoa New Zealand: a scoping review protocol

2024· other· en· W6925473368 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2024
Typeother
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAotearoaProtocol (science)Scope (computer science)Rural areaInclusion (mineral)Resource (disambiguation)Clinical PracticeFocus groupRural health

Abstract

fetched live from OpenAlex

Review objective: The objective of this review protocol is to scope the extent and type of evidence describing evaluations of clinical practice guidelines, protocols, and pathways that are utilized in the rural and remote areas of Australia, Canada, and Aotearoa New Zealand. Review questions: The review will seek to answer the question: How are clinical practice guidelines, protocols, and pathways used in the rural and remote areas of Australia, Canada, and Aotearoa NZ being developed, implemented, and evaluated? Additionally, the review will address the following sub-questions: Are the clinical guidance resources (CGRs) being newly developed, adopted or adapted (contextualized) from other contexts and quality tested? What strategies are employed to implement the CGRs, and how are they selected and applied? What approaches and theories are being used to underpin the evaluations? Inclusion Criteria: Studies will be included from three high-income countries which have rural or remote regions and First Nations populations. Studies will only be included if they explicitly identify the CGR, have the resource as a primary focus of the evaluation, and show that the CGR has been endorsed or implemented for use in the rural or remote health service. Evaluations of point of care testing instruments will be excluded, as will studies conducted in aged care facilities, even if they take place in rural and remote areas.

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)0.008
metaresearch head score (Gemma)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.720
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.274
GPT teacher head0.585
Teacher spread0.311 · 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.

Study designNot applicable
Domainnot available
GenreProtocol

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

Citations0
Published2024
Admission routes1
Has abstractyes

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