Bibliographic record
Abstract
the article by Dr. Emmott and the editorial “A warm place to practise: meeting the challenges of medicine in the North, ” by Dr. Allon Reddoch (CMAJ 1998;158[2]:337-8). The hor-rors of the former are finely balanced by the call of the latter to take a cre-ative breather in a northern setting. Nothing is known about the ef-fects of a locum tenens on patient care, despite the enormous number of patient–locum encounters that take place annually. One can only guess at the measurable rewards and hazards encountered by the replace-ment locum and the surprises await-ing the returning incumbent. Simple evaluative literature is yet to be writ-ten, and serendipity alone determines what might loosely be termed success or failure. The arrival of a locum can provide a valuable opportunity for professional enrichment and CME, gentle peer evaluation (in both direc-tions), exposure to new populations and challenges, and reflection on the most effective ways of delivering health care. When things go badly, poor communication, unrealized ex-pectations, financial catastrophe and irreparable harm to patient care may be involved. Many of us know of an enthusiastic locum who, in a matter of weeks, has reduced a flourishing practice to a small band of loyal fol-lowers genuinely sorry to see him (or her) depart for new pastures. It would be instructive to take the experience beyond the level of anec-dote. As I limber up for a new season of locum negotiations, I wonder whether any colleagues feel that this common player in the Canadian medical scene deserves more careful evaluation.
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 | 0.001 | 0.014 |
| 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 | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.332 | 0.201 |
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".