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Record W4322631511 · doi:10.1093/pch/pxac101

L’anxiété chez les enfants et les adolescents – partie 1 : le diagnostic

2023· article· fr· W4322631511 on OpenAlexaffabout
Benjamin Klein, Rageen Rajendram, Sophia Hrycko, Aven Poynter, Oliva Ortiz-Alvarez, Natasha Saunders, Debra Andrews

Bibliographic record

VenuePaediatrics & Child Health · 2023
Typearticle
Languagefr
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsCanadian Paediatric Society
Fundersnot available
KeywordsHumanitiesPsychologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Résumé Les troubles anxieux sont les problèmes de santé mentale les plus courants chez les enfants et les adolescents canadiens. La Société canadienne de pédiatrie a préparé deux documents de principes qui résument les données probantes à jour sur leur diagnostic et leur prise en charge. Ces documents contiennent des conseils fondés sur des données probantes afin d’aider les professionnels de la santé à prendre des décisions à l’égard des soins aux enfants et aux adolescents atteints de ces troubles. La première partie, qui porte sur l’évaluation et le diagnostic, vise à1) passer en revue l’épidémiologie et les caractéristiques cliniques des troubles anxieux; 2) décrire un processus d’évaluation des troubles anxieux. Des thèmes précis sont abordés, y compris la prévalence, le diagnostic différentiel, les affections concomitantes et le processus d’évaluation. Des démarches sont proposées pour standardiser le dépistage, recueillir l’anamnèse et observer le patient. Des caractéristiques et indicateurs connexes, qui distinguent les troubles anxieux des peurs, inquiétudes et sentiments d’anxiété adaptés au développement, sont examinés. Il est à souligner que, dans le présent document, le terme « parent » (au singulier ou au pluriel) inclut les personnes qui s’occupent principalement de l’enfant et toutes les configurations familiales.

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)0.002
metaresearch head score (Gemma)0.008
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: Review · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.034
GPT teacher head0.326
Teacher spread0.292 · 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
GenreReview

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
Published2023
Admission routes2
Has abstractyes

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