Building a CTU Orientation Handbook iPad® application for first-year residents
Bibliographic record
Abstract
The General Internal Medicine Clinical Teaching Unit (CTU) is a challenging rotation for new residents and the optimal format of orientation has not been determined. We hypothesized that an iPad® application (app) would be a useful reference tool after residents completed their traditional large group orientation.Postgraduate year 1 (PGY1) residents were sent a link to download the free app one week before the start of their rotation. A pre-usage survey at initial login collected basic demographics. Usage data was collected to determine the sections, duration, and the timeframe from which the app was utilized.Pre-usage survey data revealed that 63% of participants were female, 69% felt the app would improve orientation, and 94% were comfortable using mobile technology for medical education. Usage data showed "Teaching Sessions and Schedules," "The Consult Note," and "Admission Orders" were the three sections most commonly used. The most usage was during the evening call shift (10pm to 6am), followed by the morning shift (6am to 5pm).The CTU Orientation App was a useful supplement to the traditional orientation. Researchers may not be able to predict what content would be most valuable in an iPad® app, thus pre-development needs-assessments and usage feedback are crucial.
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 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 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.002 |
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 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".