Web-Based Software to Assist in the Localization of Neuroanatomical Lesions
Bibliographic record
Abstract
OBJECTIVE: To evaluate the educational effectiveness of a novel, web-based neuroanatomical localization application. METHODS: A prototype version of a neuroanatomical localization application was developed, limited to lesions involving Cranial Nerve (CN) VII. Second year medical students at the University of Ottawa were recruited to participate in the study. Participants were exposed to a didactic teaching session on CN VII anatomy. They were subsequently randomized to two groups - one group was granted access to the localization application (the "intervention group"), while the other group was given a booklet of standard textbook resources (the "control group"). Participants then completed a case-based multiple choice test on localization of neurologic lesions associated with CN VII, followed by a questionnaire regarding the experience. RESULTS: Thirty-nine students volunteered to participate. Twenty were randomized to the intervention group and 19 to the control group. There was a mean test score difference of 1.3 (CI.95=0.2, 2.3) that was significantly higher in the intervention group when compared to the control group. Significance was determined by a Wilcoxon rank test (p=0.028). Questionnaire results were similar for both groups, showing an overall favourable evaluation of the localization application. CONCLUSIONS: The results support our hypotheses that students using the application would perform better on the multiple choice question (MCQ) test and there would be an overall preference for its use. The demonstrated educational benefit of the application, in addition to the demand for such a resource expressed by the participants, warrant further investigation into the development of a neurological localization application.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".