A Treatment Program for Individuals With Deficient Evaluative Processing and Consequent Impaired Social and Risk Judgement
Bibliographic record
Abstract
The current study evaluated the effectiveness of a rehabilitation program developed to assist individuals such as AM who have impaired social and risk judgement. AM's difficulties developed after a severe traumatic brain injury that resulted in bilateral frontal and temporal lobe damage including damage to the amygdala. Previous work (Park et al., 2001) established that AM had impaired automatic processing of negative, but not positive evaluative information, and relatively spared processing of both types of evaluative information when using controlled or strategic processing. In the Strategic Evaluation of Alternatives (SEA) treatment program, AM was trained to compensate for his impairments by explicitly retrieving positive and negative attributes associated with potential actions prior to performing them. The SEA treatment focused specifically on improving AM's ability to obtain financial compensation for his work-related activities. Results showed improved performance on work-related activities and evidence of generalization. Analyses suggested that the process underlying improved performance was compensatory rather than restorative in nature. We discuss the implications of these results for the development of rehabilitation treatment for patients with impaired social and risk judgement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".