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Record W4394931240 · doi:10.1002/cl2.1400

PROTOCOL: The efficacy of nutritional interventions in reducing childhood/youth aggressive and antisocial behavior: A systematic review and meta‐analysis

2024· review· en· W4394931240 on OpenAlexaff
Barna Konkolÿ Thege, Eden Kinzel, Jamie Hartmann‐Boyce, Olivia Choy

Bibliographic record

VenueCampbell Systematic Reviews · 2024
Typereview
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsWaypoint Centre for Mental Health CareUniversity of Toronto
Fundersnot available
KeywordsPsychological interventionIntervention (counseling)AggressionProtocol (science)Meta-analysisPsychologyClinical psychologyDevelopmental psychologyMedicinePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

This is a protocol for a Campbell systematic review of intervention effectiveness. The goal of this systematic review is to answer the following questions based on the available empirical evidence: Are there nutritional interventions (dietary manipulation, fortification or supplementation) that can reduce excessive aggression towards others in children/youth? If yes, how strong is their effect and is there a difference among the three intervention types? Are there nutritional interventions that can reduce antisocial behaviors in children/youth? If yes, how strong is their effect and is there a difference among the intervention types? Are there nutritional interventions that can reduce violent offending in children/youth? If yes, how strong is their effect and is there a difference among the intervention types? Are there nutritional interventions that can reduce non-violent offending in children/youth? If yes, how strong is their effect and is there a difference among the intervention types? What implementation barriers and solutions to these exist in relation to the above nutritional interventions in children/youth?

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)0.068
metaresearch head score (Gemma)0.145
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.148
Threshold uncertainty score0.494

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.145
Meta-epidemiology (narrow)0.0080.007
Meta-epidemiology (broad)0.0270.026
Bibliometrics0.0110.012
Science and technology studies0.0040.005
Scholarly communication0.0110.010
Open science0.0050.006
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.1480.017

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 head0.176
GPT teacher head0.435
Teacher spread0.259 · 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 designMeta-analysis
Domainnot available
GenreProtocol

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

Citations2
Published2024
Admission routes1
Has abstractyes

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