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Record W2100437681 · doi:10.1093/jpepsy/jsn043

Examining Short-term Stability of the Mealtime Interaction Coding System (MICS)

2007· article· en· W2100437681 on OpenAlexfundno aff
Monica J. Mitchell, Carrie Piazza‐Waggoner, Avani C. Modi, David M. Janicke

Bibliographic record

VenueJournal of Pediatric Psychology · 2007
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Mental HealthMcMaster University
KeywordsObservational studyEveningPsychologyCoding (social sciences)CorrelationClinical psychologyPsychometricsDevelopmental psychologyMedicineInternal medicineStatistics

Abstract

fetched live from OpenAlex

OBJECTIVE: This study assessed the stability of ratings on the McMaster Mealtime Interaction Coding System (MICS), an observational measure of family functioning, across three typical evening meals. METHODS: Participants included families of infants and toddlers with cystic fibrosis (n = 33) and with no chronic illness (n = 33). Three meals were videotaped across a 3-week period (M = 17.4 days) and involved a secondary data analysis from a larger study. RESULTS: Across both groups, test-retest reliability (paired correlation coefficients) was generally moderate, but significant, for all scales at each time point comparison. Analyses revealed no significant within-or between-group differences across time periods on healthy versus unhealthy ratings. CONCLUSIONS: This study highlights the limitations of coding a single mealtime observation or interpreting multiple observations using the MICS. Findings highlight that family, meal, illness, and assessment factors may impact variability in ratings over time.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.246

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.094
GPT teacher head0.374
Teacher spread0.280 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations19
Published2007
Admission routes1
Has abstractyes

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