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
You are working at triage and a bed has just become available in the department. according to Canadian Triage and acuity Scale (CTaS) guidelines, which of the following patients should be assigned the highest triage score and assigned to the available bed? A. 25-year-old male with 10 cm laceration to right forearm from skill saw blade. Pressure dressing in place, bleeding controlled. Neurovascular status to the right upper limb is intact. Pain level is 4/10. B. 40-year-old male with "heartburn" after playing hockey. He went out for beer and wings after the game. He arrives pale and nauseated, with a serum glucose level of 11 mmol/L. His past medical history includes diabetes and heavy smoking. He denies drug use. C. 70-year-old female with fractured left hip from fall at home, standing height. Left leg is externally rotated and shortened. Neurovascular status to the left lower limb is intact. Vital signs are stable; alert and oriented. Pain level is 5/10. D. 28-year-old female with mild abdominal cramping and moderate vaginal bleeding at 13 weeks gestation. Blood pressure (BP) is 100/60 mmHg, heart rate (HR) is 94 beats/minute (bpm), and temperature (Temp) is 37.3 o C. She is anxious and crying; her husband is with her.
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 | 0.000 | 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 | 0.000 | 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) | 0.010 | 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