Bibliographic record
Abstract
CANADIAN FEATURES AT THE TORONTO INTERNATIONAL FILM FESTIVAL 2004 Again I looked for interesting Canadian productions at Toronto's International Film Festival 2004. This year, sad to relate, I found only few that warranted even faint praise. At the top of my list was the Festival's gala opener, Being Julia, produced by Robert Lantos - his second venture with Hungarian director István Szabó and like the first, Sunshine, Being Julia is set outside Canada. It's an adaptation of an almost forgotten Somerset Maugham novel, the story of Julia Lambert, an ageing but not yet fading diva of the London stage in the 1930s. I found Being Julia absorbing, amusing and with an extraordinary sense of location and period. Clean, directed by France's Olivier Assayas, is a Canadian film in the sense that the character of Albrecht as played by Nick Nolte typifies the kind of Canadian who would support peacekeeping,...
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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 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.629 | 0.225 |
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".