546 COMMUNITY HEALTH INITIATIVE BY UNIVERSITY STUDENTS: SYSTEMIC CHART REVIEW 2006.
Bibliographic record
Abstract
CHIUS (Community Health Initiative by University Students) is an interdisciplinary, student-run program at the downtown community health clinic (DCHC) in the downtown east side (DTES) area of Vancouver. Students from different health care disciplines work together to provide patient care under the supervision of their respective health care professions. The student clinic runs every weekend and generally involves an abundance of clinical and social encounters. After treating patients, medical students complete patient charts in the SOAP format, and all team members complete a patient encounter log. Due to growth of the team, a new clinic site, and changes to the structure of CHIUS in the last 4 years, as part of our continuing responsibility to ensure the delivery of quality patient care, student education, and public safety, we are doing a systemic review of the patient charts and encounter logs of the last 4 years. With this, we hope to confirm or further describe the demographics and needs of our patients. We hope that the outcomes of our continuing efforts will allow us to make recommendations to CHIUS that result in further tailoring of programs to meet patient needs and optimize student learning. These results are also important to ensure that the patient9s encounter with the clinic results in the most appropriate care and that we are meeting the patient9s concerns.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.011 |
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".