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'Confiabilidade inter-avaliador' da escala motora infantil de alberta em crianças de termo e pré-termo na província de talca, Chile

2010· article· pt· W241356365 on OpenAlexaboutno aff
Loreto Quezada-Villalobos, Ivannia Soto-García, Máximo Escobar‐Cabello, Antonio López-Suárez

Bibliographic record

VenueDesafíos (Universidad del Rosario) · 2010
Typearticle
Languagept
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesMedicinePhilosophy

Abstract

fetched live from OpenAlex

Purpose: To examine the ‘interrater reliability’ of the Alberta Infant Motor Scale (AIMS) in term and preterm born infants between 10 to 16 months age from Talca province, Maule Region - Chile. Subjects: 115 infants between 10 to 16 months age were incorporated to the study; 95 term born infants were attended in the local Health Centre in Talca City, and 20 preterm infants belonged to the Premature Infants Follow-Up Programme of Talca Regional Hospital. Methods: The motor behaviour of each infant was recorded and later it was assessed by two trained assessors using AIMS. It was obtained the total AIMS’ score and also from prone, supine, seated, and stand subscales. For ‘interrater reliability’ analysis it was used the Intraclass Coefficient of Correlation (ICC), the Standard Error of Measurement (SEM) and 95% limits of agreement. Results: The obtained ICC for the total scores AIMS were major than 0.94 (p<0.0002) for term and preterm born infants. The SEM of total scores was less than 3.1 points, higher than what was found in other similar studies. The 95% limits of agreement were +5.3 to -4.1 points and +7.7 to – 3.9 points in term and preterm born, respectively, revealing ‘interrater agreement’. Conclusion: The AIMS showed adequate ‘interrater reliable’ levels when was applied in Chilean term and preterm born from 10 to 16 month’s age.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.249
Teacher spread0.240 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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