Assessment of strategic self-regulation in traumatic brain injury: Its relationship to injury severity and psychosocial outcome.
Bibliographic record
Abstract
Standard neuropsychological tests administered in a constrained and artificial laboratory environment are often insensitive to the real-life deficits faced by patients with traumatic brain injury (TBI). The Revised Strategy Application Test (R-SAT) creates an unstructured environment in the laboratory in which environmental cues and internal habits oppose the most efficient strategy, thus mimicking the real-life situations that are problematic for patients with TBI. In this study, R-SAT performance was related both to severity of TBI (i.e., depth of coma) sustained 2-3 years earlier and to quality of life outcome as assessed by the Sickness Impact Profile. This relationship held after accounting for variance attributable to TBI-related slowing and inattention. These findings support the validity of the R-SAT and suggest that behavioral correlates of quality of life outcome in TBI can be assessed in the laboratory with unstructured tasks.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".