Bibliographic record
Abstract
His condition was deteriorating rapidly. Mr. James was in his late 50s and had end-stage liver disease as a result of chronic alcohol use. Throughout the admission, he had been very confused and disoriented, or encephalopathic, which was a harbinger that the end was on the horizon. One day, when Mr. James was more lucid, I was tasked with speaking to him about his wishes for resuscitation. Although this conversation is a routine occurrence on any internal medicine rotation, it would be my first time independently having a “code status” discussion with a patient. I approached his bed at the far end of a dimly lit room with the curtains drawn. He lay there motionless. The poignant yellow hue of his skin spelled out his diagnosis. There was a middle-aged woman at his bedside, but judging by her scrubs, she was a hospital employee who was there to monitor him, not a friend or family member. His arms were crossed, his eyes closed. “Mr. James,” I began. “Mr. James, I am here from the medical team to speak with you.” I spoke with him about his understanding of his prognosis and his views regarding resuscitation if and when he might need it. Not unexpectedly, Mr. James did not desire any form of advanced lifesaving maneuvers. I was thankful that the hospital sitter was there to witness the conversation and documented his wishes in his chart. Yet while Mr. James seemed to understand his precarious health status, I am not sure that I processed his dire situation, even amidst these discussions. Unbeknownst to me, this conversation would be the last time I would see Mr. James. The following week, as we were running through our list of patients one morning, I noticed that we skipped over Mr. James, even though his name was still there. I learned from my classmate who was on-call the night before that Mr. James had been found lifeless without vital signs and pronounced dead at 4:00 am. In the early hours of the morning, he had died, without a single family member or friend around. Even the person listed as his emergency contact had been unreachable. I lamented how, prior to that weekend, Mr. James had existed on this earth. We had had a conversation. Yes, he had been ill, but he was still a living, breathing human being. Yet today, the only remaining vestiges of him were mere ink markings on a page, which we had quickly skipped over as we had forged on with the next patient on our list. Mr. James tragically departed from the world alone. It was my first time experiencing a patient’s death, and I needed time alone to reflect on it. I knew this rendezvous with mortality was inevitable and that it certainly would be only the first of many such experiences throughout my medical career. I stepped outside the confines of the hospital for a breath of fresh air. I needed to gather myself. This experience reminded me that grieving and loss are inescapable dimensions of the human experience, yet they are often a silent undertone in the practice of medicine. As current trainees and future physicians, there are undoubtedly times when we need to push forward at full speed. However, there are also times, albeit brief ones, when we need to take a few moments to gather ourselves and our thoughts, particularly when we are confronted with situations such as the loss of the very essence of human existence that we so vehemently work to preserve. Acknowledgments: The author thanks Dr. Baruch Jakubovic for helpful input and guidance on this essay and for encouragement and mentorship as the chief medical resident.
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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.017 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".