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Record W1952635850 · doi:10.1002/0471264385.wei0802

Disorders of Childhood and Adolescence

2003· other· en· W1952635850 on OpenAlexaff
Eric J. Mash, David A. Wolfe

Bibliographic record

VenueHandbook of Psychology · 2003
Typeother
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsWestern UniversityUniversity of Calgary
Fundersnot available
KeywordsPsychopathologyAnxietyPsychologyDiagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early ChildhoodMood disordersBiological psychopathologyDevelopmental psychopathologyChild psychopathologyClinical psychologyDevelopmental psychologyPsychiatryPrevalence of mental disorders

Abstract

fetched live from OpenAlex

Abstract Current knowledge of child and adolescent disorders is compromised by a lack of child‐specific theories. Despite the increasing attention to disorders of childhood and adolescence, there remain fewer categories for diagnosing mental disorders in children than in adults. Despite these caveats, tremendous advances have been made in the last decade with respect to childhood psychopathology. New conceptual frameworks, new knowledge, and new research methods have greatly enhanced our understanding of childhood disorders. This chapter demonstrates these advances with respect to the broad domains of externalizing disorders (e.g., disruptive behavior disorders) and internalizing disorders (mood and anxiety disorders). Considered within this chapter are the phenomenology, epidemiology, developmental course, associated features, and proposed causes. Integrative developmental pathway models for attention deficit hyperactivity disorder and anxiety disorders of childhood are provided. The chapter concludes with a discussion of current issues and future directions for the field.

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.010
GPT teacher head0.279
Teacher spread0.269 · 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
GenreOther

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

Citations22
Published2003
Admission routes1
Has abstractyes

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