Bibliographic record
Abstract
Outside his home on the spectacular north shore of Prince Edward Island — with its sunset view to the northwest, gulf horizon due north and marram grass dunes above — Duncan Mcintosh contemplates reinvention. In a burst of light on water, flocks of migratory waterfowl circle Stanhope Bay, lower knee-locked landing gear, spread webbed feet, stretch long necks, then settle perfunctorily on the surface. Amid much flap, squawk and chatter, Canada geese, mallards and blue-winged teal soon settle into spring routines, courting on the surface, up-ending to feed below, their airy, fluid patterns driven by tide, current and wind. Bald eagles, osprey and hawks circle overhead. A red fox bitch parades her four tumbling pups. Four years on, the grace and beauty of PEI’s spring awakening continues to intrigue Duncan. “Who,” he wonders, “choreographs this miraculous ballet?” Interesting question from Mcintosh, a director/producer as comfortable directing the Shaw Festival’s classically trained veterans as choreographing and directing the shiny new singer/dancer/actor cast of the remount of his production of Island impresario Campbell Webster’s new L.M. Montgomery—based hit musical, Anne and Gilbert.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 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".