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Record W3165005042

Physical activity throughout pregnancy: guideline critical appraisal and implementation tool.

2021· article· en· W3165005042 on OpenAlexaffabout
Gaelan Connell, Carol Ann Weis, Heather Hollman, Kelsey Nissen, Leslie Verville, Carol Cancelliere

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsCentre for Disability Prevention and RehabilitationUniversity of New BrunswickUniversity of VictoriaOntario Tech UniversityCanadian Memorial Chiropractic College
Fundersnot available
KeywordsGuidelineMedicineQuality (philosophy)Family medicineLibrary scienceComputer sciencePhilosophyPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: The 2019 Canadian guideline for physical activity throughout pregnancy provides evidencebased recommendations to promote maternal, fetal, and neonatal health. We aimed to 1) critically appraise the 2019 Canadian guideline for physical activity throughout pregnancy; and 2) develop a guideline summary for clinicians to facilitate the uptake of recommendations into practice. METHODS: We used the Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument to critically appraise the quality and reporting of this guideline. Four reviewers independently scored between 1 (strongly disagree) to 7 (strongly agree) for 23 items organized into six quality domains. RESULTS: AGREE II quality domain scores ranged from 47%-64% and the overall quality of the guideline was rated as 83% (high quality). CONCLUSION: Based on its methodological quality, we recommend the use of this guideline. Our guideline summary includes six recommendations and other safety precautions that are relevant for clinicians in Canada.

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)0.158
metaresearch head score (Gemma)0.435
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 score0.158
Threshold uncertainty score0.836

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1580.435
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0060.009
Bibliometrics0.0150.014
Science and technology studies0.0050.003
Scholarly communication0.0070.005
Open science0.0080.006
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0090.004

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 head0.041
GPT teacher head0.409
Teacher spread0.367 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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