Bibliographic record
Abstract
The office visit was drawing to a close. We had discussed switching medications to control her osteoarthritic knee pain and reviewed how the surgeon was managing her continued drainage from a recent umbilical hernia repair. As I was preparing to hand her the paperwork to go to the checkout desk, she asked me how long I had been caring for her. I replied, “About 5 or 6 years,” without much thought. Mrs. M responded, “Oh, much longer.” As usual, when our memories disagreed about the facts of her care, she was right. I had provided care for Mrs. M for close to a decade. During that time, she had experienced considerable decline in her mobility because of her arthritis and began to require a walker several years ago. But she was bright and articulate and particularly loved trading barbs with me. We both loved dogs; her passion was Rottweilers, while I have a penchant for Labrador Retrievers. I think she also had a thing for intellectual Jewish men. She married one more than 50 years ago. Several years ago, he began to suffer the effects of cerebrovascular disease and eventually renal failure. His demise was slow and miserable. Perhaps for the first time in her life, Mrs. M was helpless as she watched her husband slip through the hands of the best that medicine could offer at the end of the twentieth century. Confronted with this helplessness, during these admissions, she became a terror on wheels—those of her front-wheeled walker. The house staff could hear her moving down the hall and would duck into a conference room or a stairwell, safely out of sight. Otherwise, they would be trapped beside a complaint factory of displaced anger. Many of the issues she raised were real and reflected the imperfections of hospitals, especially teaching hospitals, where errors occur and the “hoteling” functions of food and personal service are less than hospitable. Nevertheless, these were really side issues, distractions that allowed her to assign blame for a process that was awful yet inherently blameless. Her husband died 18 months ago and Mrs. M began her bereavement. As expected, the process was not easy. Her anxiety and considerable depressive symptoms have been managed with medications and counseling. Now she tells me, “David, you have no idea how hard it is to live without him.” Empathetically, I say that “I do” and recall some of the major losses in my life, losses that triggered depressive episodes, losses where the person haunted my daily thoughts for years. She counters, “No, you don't.” And I realize that again she is right. I cannot fathom the size of the emptiness in her life. As a geriatrician, I have encountered this situation on many occasions. Typically, the couple has been married for longer than 5 decades, and sometimes there are no children. It seems that couples who never bore children develop a special intertwining. Children disperse the intimacy held between two adults. Offspring need their share of attention, and as a result, married people who have children learn to distribute their love and dependence beyond a single spouse. Not so for those married without children. Perhaps Mrs. M's story is so compelling—or more accurately, threatening—to me, because I am married without children. This could be my wife or me in 30 years. Thirty years is not that far away. I can remember 30 years ago like it was yesterday. Now in my 50s, I understand the thinking behind suicide pacts and hear the voices of my patients who tell me that they have lived long enough and it is time for them to die. After Mrs. M leaves, I think about what I can and cannot do for her. I can adjust her medications and ensure that she has a good counselor. I can encourage her to participate in activities where she can meet people of all ages with similar interests. If I am lucky, I can smooth out some of the dips in brain neurotransmitters that make her feel so distraught. But there is nothing I can do to fill the hole that remains in this woman's heart. Financial Disclosure: There are no financial disclosures to report. Author Contributions: Dr. David Reuben is the sole author of this contribution. Sponsor's Role: No sponsor for this paper.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.287 | 0.142 |
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".