Bibliographic record
Abstract
I do not remember all the deliveries I have attended, but some stick out; one in particular that was not especially difficult or triumphant. Of course, it was joyous, as to be expected, with a lovely baby girl to show for it. I remember it for other reasons. It was cold and over the hours I had been in the hospital attending my primip, freezing rain had fallen. Slippery in the parking lot but not atrocious or so I thought. I chiselled my way into the car, scraped the windshield into at least some semblance of visibility and headed home. I was perhaps a bit distracted by the pleasant delivery. I was pretty much on autopilot when I went down the hill, so I really did not clue in. Well, I did not clue in until I was well past the point of no return. There was some momentary anxiety when I realized that my ability to control my car was compromised. I was not going fast at all (I was not entirely unaware) but gravity and a low coefficient of friction made me come to peace with physics quickly. Luck or my steering inputs had me slowly slide into the ditch rather than the lake, far off at the bottom of the hill. Exiting the car I determined, with great insight, that it was difficult to actually walk anywhere. The ditch offered the best traction. By the bye, a patient of mine was able to pull me out (but only after the town's sander had come by!). In the end, I was able to go back home to bed, and as it was over New Year's, I was able to sleep in (bonus). In the years to follow, I saw both mom and the growing girl on many an occasion. Sometimes out in public. Sometimes, I saw them socially. Sometimes in the office for well-baby visits or the inevitable respiratory tract infection. Over time the little girl grew up and left town to seek ambition elsewhere (as many bright young children from these parts do). I ask, and am kept periodically up to date, about her progress from Mom. Mom's retired now and apart from boredom in the depths of the pandemic, she is enjoying every minute. She is healthy, on no medications and I do not see her that often. In truth, there is no need. However, when I do see her, I am reminded of a wonderful delivery that occurred 30 years ago and, more importantly, all the details of life that happened subsequently. It may not be a particularly extraordinary story, but my practice is full of them. It is the richness of these types of stories, these types of memories and these types of relationships that I find so fulfilling. It's this connection that gives meaning to the work of a rural generalist physician. I am truly thankful for having the opportunity to be one. We have a wonderful profession.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.260 | 0.115 |
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".