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Record W7098770417

Canadian Acute Respiratory Illness and Flu Scale (CARIFS)

2016· article· en· W7098770417 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMachine Learning in Bioinformatics
Canadian institutionsnot available
Fundersnot available
KeywordsMalayIntraclass correlationRespiratory illnessReliability (semiconductor)AsthmaSeverity of illnessScale (ratio)Concordance
DOInot available

Abstract

fetched live from OpenAlex

Background: The Canadian Acute Respiratory Illness and Flu Scale (CARIFS) is a parent-proxy questionnaire that assesses severity of acute respiratory infections in children. The aim was to (a) perform a cross-cultural adaptation and (b) prove that the Malay CARIFS is a reliable tool. Findings: The CARIFS underwent forward and backward translations as recommended by international guidelines. A pilot study was performed on the harmonised version and the final version of the Malay version of CARIFS was produced. A test-retest, 1 h apart, was then performed on parents with children less than 13 years old, admitted with a respiratory tract infection. Parents of children with asthma and who were not eloquent in Malay, were excluded. The data was analysed for consistency (Cronbach’s alpha) and reliability (test-retest co-efficient). Thirty-three parents were recruited. Children were aged median (IQR) 6 (2.8, 13.3) months with a male: female ratio of 22:11 and 88 % were Malays. Parents were interviewed at median (IQR) 6 (3, 11.5) days of admission. The Cronbach’s α coefficient was 0.70 for all items. The test–retest reliability analysis had a minimum and maximum intraclass correlation coefficient of 0.63 and 0.97 respectively. Clinically, the longer patients were admitted, the lower the severity score (r = −0.35, p < 0.05), indicating that they were getting better. Conclusion: The Malay version of CARIFS is a valid and reliable tool to determine severity of respiratory illness in children. Parent-centred questionnaires are useful and should be an adjunct to other methods, in monitoring response to treatment.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.498
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.003
GPT teacher head0.224
Teacher spread0.220 · 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
GenreMethods

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
Published2016
Admission routes1
Has abstractyes

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