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Record W3108940288 · doi:10.3389/fpubh.2020.567907

Rapid-Cycle Evaluation in an Early Intervention Program for Children With Developmental Disabilities in South India: Optimizing Service Providers' Quality of Work-Life, Family Program Engagement, and School Enrollment

2020· article· en· W3108940288 on OpenAlexafffund
Dinesh Krishna, Sankar Sahayraj Muthukaruppan, Aravind Bharathwaj, Ramasubramanian Ponnusamy, Bala Murugan Poomariappan, Sathiya Mariappan, Ayesha Beevi, Janna MacLachlan, Zoé Campbell, Chamila Anthonypillai, Marie Brien, Cathy Cameron, Marina Flatman, Lesley Perlman, Stephanie Seilman, Abhinayaa Jeyapragash, Lotte van der Haar, Joachim Krapels, Sankara Raman Srinivasan

Bibliographic record

VenueFrontiers in Public Health · 2020
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsCARE CanadaUniversity of Toronto
FundersFundação Maria Cecilia Souto VidigalPalix FoundationUBS Optimus FoundationGrand Challenges CanadaBernard van Leer FoundationUniversity of TorontoAga Khan Foundation CanadaELMA FoundationAga Khan FoundationBill and Melinda Gates Foundation
KeywordsService providerMedical educationService delivery frameworkNursingIntervention (counseling)Data collectionFocus groupProgram evaluationService (business)MedicinePsychologyBusiness

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.220
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.163
GPT teacher head0.412
Teacher spread0.250 · 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

Citations24
Published2020
Admission routes2
Has abstractyes

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