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Record W3172027974 · doi:10.1177/17579139211018724

Knowledge into action: proposing an evidence-based group prenatal exercise prescription

2021· review· en· W3172027974 on OpenAlex
Miguel Sánchez‐Polán, TS Nagpal, Rubén Barakat

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

VenuePerspectives in Public Health · 2021
Typereview
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSession (web analytics)Medical prescriptionRandomized controlled trialMedicineExercise prescriptionPhysical therapyNursingComputer science

Abstract

fetched live from OpenAlex

AIMS: In accordance with the American College of Obstetricians and Gynaecologists recommendations for exercise during pregnancy, this article provides an evidence-based prescription for a group-based prenatal exercise programme. METHODS: This prescription has been tested in 21 randomized controlled trials. This short report outlines in detail the seven components included in each session (warm-up, aerobic training, resistance training, coordination and balance, pelvic floor training, cool-down, and final discussion). RESULTS: Using the 26-item behaviour change taxonomy proposed by Abraham and Michie, we identified common techniques that are employed in each session to provide a rationale for the high-programme adherence. CONCLUSIONS: This session model can be replicated to design prenatal exercise programmes with high adherence and that can be offered by trained exercise professionals.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.285
GPT teacher head0.489
Teacher spread0.203 · 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