Bibliographic record
Abstract
newsman Stanley Burke interviewing dairy farmer Ted Boorsma / 20 3 Members of GroupAction to Stop Pollution promoting its first meeting, December 1967 / 32 4 Public inquiry into the apparent pesticide-induced death of ducks off of the Toronto Islands, July 1969 / 46 5 "How would you like a glass of Don River water?" advertisement in the Toronto Telegram, 29 September 1969 / 53 6 The Don River funeral, held on 16 November 1969 / 54 7 Simon Greed, a wealthy industrialist portrayed by Pollution Probe member Tony Barrett / 54 8 Placement of a wreath at the conclusion of the Don River funeral / 54 9 Pollution Probe meeting with Robert Stanfield, leader of the Progressive Conservative Party of Canada, 1970 / 61 10 Brian and Ruth Kelly, members of Pollution Probe's Summer Project '70, who travelled throughout cottage country / 67 11 Pollution Probe buried a time capsule outside the present-day John P.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.815 | 0.720 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".