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Record W3138111944 · doi:10.1016/j.ijnss.2021.03.005

Supplement to the published paper “Theory-guided interventions for Chinese patients to adapt to heart failure: A quasi-experimental study”

2021· article· en· W3138111944 on OpenAlexaff
Xiyi Wang, Leiwen Tang, Doris Howell, Qi Zhang, Ruolin Qiu, Hui Zhang, Zhihong Ye

Bibliographic record

VenueInternational Journal of Nursing Sciences · 2021
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychological interventionHeart failurePsychologyMedicineGerontologyInternal medicineNursing

Abstract

fetched live from OpenAlex

Supplement to the published paper "Theory-guided interventions for Chinese patients to adapt to heart failure: A quasi-experimental study"We appreciate the question raised in a discussion with a reader and the editor about an instrument for outcome measure of the quality of life among people with chronic heart failure [1].We recognized that we should have described more details about how to convert the score of the Minnesota Living with Heart Failure Questionnaire (MLHFQ).Lack of scoring details might lead to some confusion to understand the results of this study.We thank the International Journal of Nursing Sciences for the opportunity to provide further information to clarify the process of data analysis and research findings.The MLHFQ is a well-developed scale for investigating patients' everyday living problems relevant to heart failure and their impacts on physical activity, social interaction, sexual activity, and emo-Xiyi

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)0.006
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.273
Threshold uncertainty score0.912

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.064
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.003
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.2730.035

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 head0.057
GPT teacher head0.428
Teacher spread0.372 · 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 designNon-randomized trial
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

Citations1
Published2021
Admission routes1
Has abstractno

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