Bibliographic record
Abstract
My left eye opens to a curtain of blue paper obscuring the operating room lights above. When I close my left eye again, I am surprised to see movement before my right eye, like short streams of mercury flowing across my field of vision. As the sedative wears off, I remember that an ophthalmologist is in the process of replacing my misshapen cornea with that of a donor. I relax my tense muscles a bit with the doctor's reassurance that everything is going well and that he is close to finishing his sutures. The start of my clinical years in medical school was heralded by an interest in surgical specialties. By then, the impairment in my depth perception was clear. Every suture held taut for me to cut represented a challenge. I lived in the fear that my mentors would discover my condition. I explored the possibility of corrective lenses but lacked the perseverance to wear the uncomfortable contacts. I finally entertained the thought of surgical correction. Before my surgery, I had finished two years of orthopedic residency. I took pride in my ability to counsel patients on their options, giving each a clear conscience that he or she was making an informed, empowered decision. Yet I was also struggling to learn my craft with the handicap of impaired vision. As a result, I found myself in a Toronto hospital at the sharp end of the scalpel for a change. I now realize that no matter how seamless my procedural descriptions were I could not adequately prepare patients for what they were about to experience. I thought that the combination of medical training and the precise description of the corneal transplant would give me an accurate sense of the operative and rehabilitative phases of my treatment. Despite this preparation, though, I was completely unprepared for the process. Like many of the patients I had counseled, I planned to begin normal activities soon after the surgery. Then I saw a time interval familiar to orthopedic surgeons quoted on my postoperative instruction pamphlet: six weeks. Now I was the one relegated to walking for exercise, the one whose career was resting on the results of the surgery. This experience taught me that it is not possible to empathize with patients unless you have had a similar experience. Despite our advanced training, surgeons cannot stand side-by-side with patients as they undertake the risks of surgery and follow postoperative instructions. Although I can try, I will never truly grasp the effect that injuries and illnesses have on my patients' lives and the impact of my recommendations on their dreams and aspirations. As my vision sharpens, so does my perspective. When I return to the other end of the scalpel, I will be more able to appreciate what it is that my patients are experiencing and, with what I have learned in mind, able to tailor their care. My eye surgery has given me more than just clarity of vision. Jesse Shantz, MD, MBA Dr. Shantz is a resident, Section of Orthopedic Surgery, University of Manitoba, Winnipeg, Manitoba, Canada; ([email protected]).
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 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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.243 | 0.252 |
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".