Standardizing Neurological Assessments
Bibliographic record
Abstract
Evaluation of neurological status is imperative to patient assessment. Multiple assessment tools are readily available for clinicians to diagnose and report changes in neurological condition. Some of these tools include the Glasgow Coma Scale, the National Institutes of Health Stroke Scale, the Canadian Neurological Scale, and the Four Score. Although assessment tools are beneficial to help standardize the assessment and communication of findings, they are at times cumbersome, leaving bedside clinicians with questions concerning which tool is appropriate for a given patient population. This initiative began as a means to standardize assessments and communication for neuroscience patients. As success was met, the project was moved forward locally at our hospital campus and later extended to the entire health system. With the support of the chief of neurology, the neuroscience patient care services director, the stroke coordinator, and the neuroscience clinical educator, three different neurological examinations were developed. They were defined as the Basic Neurological Check, the Coma Neurological Check, and the National Institutes of Health Stroke Scale/Stroke Neurological Check. The neurological examinations would address the assessment needs of patients with acute stroke, general neurosurgery/neurology patients, and patients in coma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.132 | 0.208 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".