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Record W2792317641 · doi:10.2196/mhealth.9509

Metadata Correction: Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation

2018· erratum· en· W2792317641 on OpenAlexvenueno aff
Thijs Vandenberk, Jelle Stans, Christophe Mortelmans, Ruth Van Haelst, Gertjan Van Schelvergem, Caroline Pelckmans, C. J. P. P. Smeets, Dorien Lanssens, Hélène De Cannière, Valérie Storms, Inge M Thijs, Bert Vaes, Pieter Vandervoort

Bibliographic record

VenueJMIR mhealth and uhealth · 2018
Typeerratum
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceMetadatamHealthWorld Wide WebInformation retrievalMedicineNursing

Abstract

fetched live from OpenAlex

[This corrects the article DOI: 10.2196/mhealth.7254.].

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)0.029
metaresearch head score (Gemma)0.415
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: Other · Consensus signal: none
Teacher disagreement score0.154
Threshold uncertainty score0.515

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.415
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.005
Science and technology studies0.0040.003
Scholarly communication0.0060.004
Open science0.0040.005
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.1540.058

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 head0.137
GPT teacher head0.507
Teacher spread0.371 · 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
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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