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Record W3197178421 · doi:10.2196/33179

Authors’ Response to Peer Reviews of “Use of Smartphone Apps for Improving Physical Function Capacity in Cardiac Patient Rehabilitation: Systematic Review”

2021· article· en· W3197178421 on OpenAlexvenueno aff
Katherine Tuttle, Arpad Kelemen, Yulan Liang

Bibliographic record

VenueJMIRx Med · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationPhysical medicine and rehabilitationFunction (biology)Computer scienceMedicinePhysical therapyPsychologyBiology

Abstract

fetched live from OpenAlex

This is the authors' response to peer-review reports for the paper "Use of Smartphone Apps for Improving Physical Function Capacity in Cardiac Patient Rehabilitation: Systematic Review".Round 1 Review I. We went through the PRISMA checklist and made changes for better compliance.Some items on the list are not applicable to our article [1].II.We created the PRISMA diagram as requested by the reviewers.III.We have done that.IV.We are fine with transferring to JMIR Cardio as suggested by some reviewers.V. We extended the Abstract as requested.

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)0.080
metaresearch head score (Gemma)0.462
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.920
Threshold uncertainty score0.424

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0800.462
Meta-epidemiology (narrow)0.0020.004
Meta-epidemiology (broad)0.0080.010
Bibliometrics0.0070.005
Science and technology studies0.0050.004
Scholarly communication0.0090.005
Open science0.0050.008
Research integrity0.0360.018
Insufficient payload (model declined to judge)0.0370.014

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 head0.055
GPT teacher head0.351
Teacher spread0.296 · 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.

Study designNot applicable
DomainEvaluation
GenreCommentary

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
Published2021
Admission routes1
Has abstractyes

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