Raconter des histoires de père en fille : portraits d’Yves et de Marie José Thériault
Bibliographic record
Abstract
Quelqu'un se mit à faire une chanson.Il parlait d'Agaguk, grand chasseur.Et il chantait aussi Tayaout qui serait bien le plus grand chasseur des temps, fils d'un tel père.La chanson dura longtemps.Agaguk s'en saoûlait.Y. Thériault, Agaguk 1 L'histoire de Didem-au-Petit-Serpent et du musicien d'Alep traversa l'univers des Croyants comme une traînée de poudre.Les chanteurs l'ont chantée.Les conteurs l'ont contée.Les poètes l'ont mise en vers qu'on a brodés sur des bannières et suspendus dans les mosquées.M. J. Thériault, « Histoire de Didem-au-Petit-Serpent et du musicien d'Alep », dans Portraits d'Elsa et autres histoires 2 Homer adossa sa chaise au mur de la cuisine et se mit à lui raconter l'histoire du dernier colonel Cary, qui avait légué l'île à l'Institut.Et qui était une femme.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".