Perseveração na Tarefa Geração Aleatória de Números para Crianças
Bibliographic record
Abstract
Inhibitory deficits are observed in several neurological and psychiatric disorders, which may increase the frequency of perseverative responses. There are no standard criteria to assess perseveration. The first study aimed to obtain preliminary data on how many blanks until the repetition of a number can be considered a perseveration in Random Number Generation (RNG) task. The discriminative potential of cutoff points was investigated by comparing children with Attention Deficit Hiperactivity Disorder (ADHD) and healthy children (Study 2). The instruments were: sociodemographic and health questionnaire, Conners Abbreviated Rating Scale, Raven Coloured Progressive Matrices and RNG. The sample was composed of children aged 6 to 12 years (Study 1: n= 60; Study 2: ADHD, n=9 e Controls, n=18). The children took on average 4.97 (sd=1.78) blanks to repeat a number. The criteria that considers perseveration as the repetition of a number up to five blanks after their last recall discriminated ADHD from controls. Therefore, this seems to be the most sensitive criteria to assess perseveration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".