Bibliographic record
Abstract
Synopsis Ali has recently been released from prison and is now working as a night watchman in Tehran. This factory job now means that he is at least able to support his small family comprising his wife Sara and their daughter, Saba. One day, Ali comes home from work to discover that Sara and Saba have disappeared. Realising that thereâs no point in waiting for them any more, Ali decides to go to the police. ************ But thereâs chaos at the police station and it takes hours for him to discover anything. Finally, he is informed that his wife was caught up in a shoot-out with demonstrators and was killed. His daughter Saba, however, is still missing. Aliâs search for his daughter drives him to distraction; he despairs still more, when, in the end, her dead body is discovered. Desperate for revenge he runs amok randomly killing two policemen. After the deed he heads for the woods in the north by car. But the police have long been on his trail; they give chase along a country road until Aliâs car crashes. Ali runs off into the woods to hide among the trees â in vain. Hassan and Azem, the two policemen who are chasing him, arrest him. Ali seems resigned to his fate and willingly follows the two men, who keep a sharp eye on him. But then, they get lost. All they can see are trees. In such a remote landscape as this, itâs hard to tell the difference between hunters and hunted. -- Berlinale Cast: Rafi Pitts, Mitra Hajjar, Ali Nicksaulat, Hassan Ghalenoi, Manoochehr Rahimi Berlinale (Competition), Melbourne (International Panorama), Toronto (Contemporary World Cinema), São Paulo (International Perspective), Stockholm (Spotlight), Mar del Plata (International Competition)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.068 | 0.024 |
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".