Establishing the Validity of the Severity Indicator Resource Utilization Scale in comparison to the Functional Independence Measure
Bibliographic record
Abstract
In the current study a resource utilization tool designed to assess the cognitive, behavioral and psychiatric consequences of brain injury, the SIRUS was compared to the FIM, which is commonly used resource utilization tool with established reliability and validity. Scores for brain injured patients were compared on both instruments as well as assessment of the psychometric properties of the SIRUS. The results demonstrated the SIRUS to be a reliable and valid tool for symptom assessment and evaluation in an inpatient ABI (traumatic and non-traumatic) population. SIRUS scores discriminate between ABI severity demonstrating non-traumatic brain injuries to be associated with poorer long term outcomes during inpatient rehabilitation. The findings would show the SIRUS to be designed for use in the ABI population and is shown to be a quick and easily administered assessment tool with established reliability and validity that can accurately determine injury severity and the resource requirements of brain injured patients. The advantage of SIRUS over other resource utilization tools is that it uniquely accounts for the cognitive, behavioral and psychiatric issues related to brain injury which is not typically accounted for in other related instruments.
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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 | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".