Bibliographic record
Abstract
SINGAPORE INTERNATIONAL FILM FESTIVAL 2004 For nearly two decades, the Singapore International Film Festival (SIFF), the showcase of Southeast Asian cinema, has also served as a timely beacon for other key Asian film festivals. Pusan in Korea, Filmex in Tokyo, and Cinefan in New Delhi have benefited from Singapore, simply because SIFF was on the scene first and did all the spadework. Link all four festivals together, and the committed cineaste can easily anticipate Asian entries selected later for Cannes, Venice, Berlin, Montreal, and elsewhere. Its secret? The SIFF is independently operated under a quartet of film professionals (Geoffrey Malone, Philip Cheah, Lesley Ho, and Teo Swee Leng), who concentrate on quality Asian cinema. The Silver Screen Awards, inaugurated in 1991, are judged by a professional jury of peers. The Asian Films section a focuses on current trends, styles, and themes in the respective national cinemas. And Singapore happens...
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.547 | 0.420 |
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".