Bibliographic record
Abstract
Savez-vous pourquoi on traite les francophones de frogs?? Connaissez-vous la signification du mot Ontario?? Quels bebes franco-ontariens sont devenus celebres dans le monde entier?? Combien de tresors se cachent dans la tourbiere d'Alfred?? Vous trouverez les reponses a toutes ces questions dans ce texte documentaire sur l'Ontario francais. Vous y trouverez aussi poeme, charade, chanson et mot mystere sur la francophonie ontarienne. L'auteure chevronnee Andree Poulin y presente les heros, l'histoire et la geographie de l'Ontario francais. Des photos d'epoque, des illustrations rigolotes et des bandes dessinees completent les informations presentees. Cet abecedaire hautement original est concu pour que les enfants apprennent en s'amusant. Ce livre raconte comment les Franco-Ontariens luttent fierement et depuis longtemps pour preserver le fait francais. Il souligne aussi l'importance d'aimer et de proteger notre magnifique langue francaise. Un documentaire captivant qui enrichira les connaissances des lecteurs de 7 a 77 ans.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 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".