Bibliographic record
Abstract
Most of us would agree with the almost trite saying that “life is a journey”. Of course it is, unless it ends tragically at birth, and even then it is a very short journey. All of us can describe how we got from one stage in life to another, whether personal, family, education or career. Many journeys seem to be in an almost straight line while others meander from one place to another, changing direction and alternating goals, sometimes zigging back and forth. I have had many wonderful journeys in my life; the choice to change career aspirations from engineering to medicine, the choice the study in medicine in Scotland, the choice to focus on geriatrics and then the choice to branch out into medical ethics to add more depth to clinical medicine. The early undergraduate study of philosophy planted the seed that eventually grew into my completing a Master’s in Medical Ethics; and then expanding my teaching and practice to include palliative care and end of life-decision-making, to most recently participating in the assessment of those requesting medical assistance in dying (MAID in Canada).
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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.064 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.007 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".