Bibliographic record
Abstract
How much is $250 worth?Maybe it's just worth the memory it buys.Maybe it's a relatively cheap investment in feeling we've done a good thing.It was the mid 1980's.I had finished my arduous residency training in neurosurgery and had recently started on staff at a large teaching hospital.I was bright-eyed and bushy-tailed, brimming with idealism and naiveté.One of the surgical patients in my first six months was a lovely man, a recent immigrant from an African country where he had been an academic.Although he spoke with an accent, his grammar was impeccable and his vocabulary elegant.Here in his new chosen home, the land of opportunity, he was forced to do more menial work.He required a complex operation for a benign condition.As his neurosurgeon, especially a "new kid on the block", I was pleased when he had a good outcome.There were one or two routine post-operative visits.Then, many months later, he requested an appointment with me.I feared he was returning due to complications from the surgery.However, he walked into my office looking just fine.He stood straight and tall and proud and was as well-dressed as usual.His beard was perfectly trimmed, as always.I don't recall the exact words we exchanged, but he was in some kind of jam and needed some urgent financial help, shortterm, one-time.As he made his request, he seemed to be much less uncomfortable than I imagined I would have been had our situations been reversed.He did not divulge any details and I did not feel it my place to ask.I don't recall the words "loan" or "borrow" being used by either of us.He did not specify an amount.I asked him to return to my office in a week.I did not want to ask a senior colleague for advice as I certainly knew what the answer would be.So I presented the dilemma to my wife.Not only was she my best friend and most trusted advisor, she was also the one person who could possibly have a stake in my decision.I was just starting on staff, my earnings were modest, we had debts, and our third child was on the way.She told me I should do whatever was in my heart.I had conflicted feelings -my instincts as a person told me to reach out to this man and help him.But my instincts as a health care professional screamed, "Are you mad? Get your boundaries straight, dude!"I slept on it for a few days.Something about this man and his situation touched me and compelled me.I felt that he was honest and decent beyond question.The day he returned to the clinic I locked the office door and handed him $250.00 in cash.I have no idea how I arrived at that amount.It seemed sufficient without being extravagant.He thanked me, said nothing else, and walked out.I made no documentation on his chart or anywhere else.The transaction was untraceable.I don't know if I did it to be philanthropic or if I was just afraid of how I would feel about myself if I denied his request.Over the months and years, I never expected or received reimbursement or any news from him.
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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.137 | 0.029 |
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".