Bibliographic record
Abstract
My clerkship year was full of firsts: My first time in a hospital setting; my first time seeing patients independently; and my first time managing patients who were acutely ill. During my surgical clerkship, I met many patients whose stories lingered in my mind long after they had left my care. Each had a unique story, but they all were stuck in the same heart-wrenching limbo between life and death. Reflecting on this limbo inspired me to create Tug of War, on the cover of this issue. A tug of war pits 2 opposing forces against each other in a test of strength and will for one force to overcome the other. Like the angel reaching toward the brightest star, my patients were reaching for something beyond the physical world. The chain around the angel’s ankle represents all the factors that were trying to pull a patient back toward life: their family and friends, and us, the physicians fighting to keep them alive. It was hard to tell which side would win, the force of nature pulling them toward the great beyond or the chain that anchored them down on Earth. I cannot speak to the experiences of the patient, family, or friends, but as the medical student on the surgical team, I found waiting and hoping day-by-day for small changes in clinical status to be excruciating. We had done all that we could, and all that was left to do was wait and see if our patient, our angel, would respond. In my digital painting, the angel is covered in cuts, her dress is torn, and her wing is broken to represent the battle wounds that she acquired during her fight for her life. Every morning, we would assess if there were any signs of improvement in our patient’s condition. Family and friends would wait at the bedside anxiously and hopefully, but as the days turned into weeks with minimal to no change, their hope slowly melted to desperation. In my digital painting, I chose to reflect this loss of hope through the sky full of stars that fall and fade into a blanket of nothingness in the foreground, like a series of unfulfilled wishes. I thought about these patients often and wondered if they had tipped in either direction. Whenever I felt disheartened about their situations, I added a bit more to the picture, and it evolved over the weeks of my surgery rotation. Pouring those emotions into art helped me come to terms with the uncertainty surrounding each prognosis and accept that our medical team provided each patient with the best care we possibly could. This piece is my tribute to my patients’ stalemate battles, their stories with indeterminate endings. Tug of War
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.306 | 0.116 |
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".