Festival international du film de Toronto : Cartes postales de Toronto
Bibliographic record
Abstract
Comme tous les trois ans, le TIFF -pour Toronto International Film Festival -invite Ciné-Bulles à passer cinq journées dans son périmètre pour prendre le pouls de cette manifestation qui, en son genre, demeure la plus importante d'Amérique du Nord.C'est dire combien, contrairement à un Festival des films du monde (FFM) par exemple, dont le généreux système d'accréditation doit garantir l'affluence du public dans les salles, le festival de Toronto pourrait, s'il le voulait, se passer de l'apport de quelques journalistes pigistes.Mais, pour l'abondance de sa programmation, qui comble les déficiences nombreuses de celle du FFM, pour la qualité de ses invités aussi, le festival de Toronto demeure un lieu de séjour incontournable.J'acceptai donc l'offre avec enthousiasme, sans savoir que le segment de festival que j'avais choisi -soit la seconde moitié, allant du 11 au 15 septembre -allait fatalement être marquée par les attentats commis contre le World Trade Center et le Pentagone...
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.083 | 0.005 |
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".