Bibliographic record
Abstract
THE 10th SOCHI INTERNATIONAL FILM FESTIVAL ASK ANY devotee of the Sochi International Film Festival, and you will hear that this innovative and visionary festival on the Black Sea, founded by Mark Rudinstein under the nickname "Kinotavr" with actor Oleg Yankovsky as festival president, far outstrips all other Russian film events when it comes to programming the best national feature films and debut productions made in the course of a year. Lately, under programming directors Sergei Lavrentiev and Andrei Plakhov, the festival has shifted into high gear until, for its 10th anniversary celebration (3-14 June 1999), it expanded its horizon to include an international competition devoted to "Young Directors" and secure the support of the nation-wide Russian TV Channel to cover the event. Indeed, this "Black Sea Riviera" with its subtropical climate, palm trees, first-class hotels, beach restaurants, and bevy of prominent guests needs only an international...
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.460 | 0.267 |
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".