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Record W4407794715 · doi:10.1093/pch/pxae089

Evaluating and caring for children with a suspected learning disorder in community practice

2024· article· en· W4407794715 on OpenAlexaff
Justine Cohen-Silver, Meta van den Heuvel, Sloane Freeman, Jacqueline Ogilvie, Tara Chobotuk

Bibliographic record

VenuePaediatrics & Child Health · 2024
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsCanadian Paediatric Society
Fundersnot available
KeywordsPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Learning challenges are common in school-aged children, with 5% to 10% meeting the criteria for a specific learning disorder (SLD, previously termed a 'learning disability'). Learning disorders can present in community practice settings as behaviour challenges, school avoidance, or as symptoms of a mental health problem. Concomitant issues may include a mental health disorder, a genetic, metabolic, or neurological condition, or developmental delay. This practice point offers guidance to paediatric health care professionals regarding the presentation and diagnosis of an SLD, including information on psychoeducational assessments, a medical workup for children with learning challenges, possible comorbid health issues, and points for improvement and advocacy in support of families and children with a range of learning issues.

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)0.009
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.030
GPT teacher head0.385
Teacher spread0.355 · 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
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

Citations1
Published2024
Admission routes1
Has abstractyes

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