CBCL/6-18 e TRF/6-18: contribuições para o processo psicodiagnóstico
Bibliographic record
Abstract
Alguns dos instrumentos mais utilizados em psicodiagnóstico de crianças/adolescentes são os questionários ASEBA. Os objetivos dessa pesquisa foram: verificar quais escalas discriminariam melhor três grupos (controle, diagnóstico neurodesenvolvimental e diagnóstico neurodesenvolvimental-emocional) e avaliar a predição diagnóstica das escalas a partir da análise discriminante. Participaram 58 crianças/adolescentes, com CBCL e TRF respondidos. As escalas que discriminaram controle e neurodesenvolvimental foram Escola e Retraimento/Depressão (CBCL) e as que discriminaram neurodesenvolvimental e neurodesenvolvimental-emocional foram Problemas Sociais (CBCL) e Tempo Cognitivo Lento (TRF). Os resultados apontaram bons valores de predição dos grupos a partir das escalas mencionadas, indicando ser uma ferramenta importante na formulação de hipóteses no psicodiagnóstico.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.010 |
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; both teacher heads agree on what is shown here.
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".