Validation of an Algorithm to Classify Urine Cultures in Family Medicine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Objectives Automation of test follow-up offers potential reductions in workload for clinicians. The primary objective of the study was to evaluate the performance of MicrobEx, a regular expression-based algorithm in classifying urine culture reports in primary care. Methods A retrospective validation of MicrobEx was performed using urine culture reports abstracted from a single academic family health team. MicrobEx classifications were compared with labels assigned manually by a human reviewer. Measures of diagnostic performance were calculated. Results MicrobEx achieved 95.3% accuracy, 88.6% sensitivity, and 100% specificity in classifying 1,999 urine culture reports. Conclusion The accuracy of MicrobEx was comparable to its performance in the original development and validation study by Eickelberg. Additional work is required to explore and improve the accuracy of MicrobEx and assess its performance across primary care settings and with more complex urine culture reports.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it