The Road Map of Animation Festival in Korea through the Comparative Analysis of 4 International Animation Festivals
Bibliographic record
Abstract
This article intends to draw the Road map of Korean International Animation Festival through the research of background and its identity of 4 International Animation Film Festivals Such as Annecy, Zagreb, Ottawa and Hiroshima. I was given opportunity to visit Annecy since 2009, it brought me to the real attraction of animation for watching of pleasure and passion of the people those who love animations. For the combining more advanced system and structure for Animation Festival in Korea, I had to do research all the information from the documents from the Annecy Collections. though I have not get the chance to go others except Annecy, However, I could get their background and history whenever I met the other Festival Committee Members. These Festivals showed us successful Road Map for the Animation Festivals in Korea as a role model. For the getting advanced system of Animation Festivals in Korea. It requires the animation theater for animation, effort for the Audiences`s Convenience and international network composition system. However, the last task of us is to make people to entertain and enjoy the animation Films, its world of attraction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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".