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Record W1966318111 · doi:10.1177/08830738050200010201

Topical Review: Developmental Screening

2005· review· en· W1966318111 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Child Neurology · 2005
Typereview
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsMcGill University
Fundersnot available
KeywordsIntervention (counseling)Screening testMedicineDevelopmental ageIdentification (biology)PopulationNewborn screeningPsychologyPediatricsDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

An estimated 5 to 10% of the pediatric population has a developmental disability. The current strategy to identify these children is through developmental surveillance, a continuous procedure in which the health professional observes the infant, takes a developmental history, and elicits any concerns that the caregiver might have. However, identification of delayed children is ineffective when based solely on routine surveillance. A necessary adjunct is developmental screening: the process of systematically identifying children with suspected delay who need further assessment. Screening tests greatly improve the rate of identification. With the advent of intervention programs and the support of organizations such as the American Academy of Pediatrics, the topic of developmental screening is a timely and essential one. This review aims to describe the properties of screening tests, to evaluate the available tools for developmental screening while providing a representative sample of the currently available developmental tests, and, finally, to evaluate the efficacy of intervention programs, a needed prerequisite to justify screening.

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.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.953
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.334
Teacher spread0.294 · 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