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Record W2081913130 · doi:10.1177/1087054707305116

Literature Review: Visual Search by Children With and Without ADHD

2007· review· en· W2081913130 on OpenAlexaff
Jennifer C. Mullane, Raymond M. Klein

Bibliographic record

VenueJournal of Attention Disorders · 2007
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDalhousie University
Fundersnot available
KeywordsVisual searchPsychologyAttention deficit hyperactivity disorderDevelopmental psychologyCognitive psychologyAudiologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To summarize the literature that has employed visual search tasks to assess automatic and effortful selective visual attention in children with and without ADHD. METHOD: Seven studies with a combined sample of 180 children with ADHD (M age = 10.9) and 193 normally developing children (M age = 10.8) are located. RESULTS: Using a qualitative approach, the authors find no group difference in automatic search, but results are variable for effortful serial search. Using a novel, graphical approach, the authors find that the ADHD group demonstrated less efficient serial search. This overall effect is explored as a function of search display complexity. Children with ADHD search less efficiently at the lowest and highest levels of display complexity. CONCLUSION: Children with ADHD show impairments in aspects of their effortful visual selective attention, as measured by visual search.

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)0.007
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: Review
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0080.009
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.040
GPT teacher head0.403
Teacher spread0.362 · 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

Citations53
Published2007
Admission routes1
Has abstractyes

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