Bibliographic record
Abstract
Three stories set across Serbia, Singapore and Spain follow immigrants and their uneasy relationships with foreign landscapes. In Serbia, a man comes back to his hometown after years living abroad. He feels estranged while visiting places he once knew well, and is confused about the disappearance of the intimate connection he had with once familiar landscapes. In Singapore, an expatriate couple living a monotonous life face upheaval after an encounter with cosplayers in their neighborhood. This is followed by a trip to a coral reef, which has managed to survive in an industrial area. In the final segment, a couple from Latin America arrives in Spain to search for a better life. They are ready to explore the new landscapes, but uneasiness and fear of the unknown haunt them. Shooting format: Super16mm Film, 1.85:1 | Sound Format: Dolby SR | Country: Singapore | Language: Japanese, Mandarin, Serbian, Spanish, English | Duration: 65 minutes produced by: Akanga Film Asia SalaMindanaw International Film Festival/ November 26 to 30, 2013 General Santos City, Philippines 42nd Montreal Festival de Nouveau Cinema, 9-20.10.2013, Montreal, Canada 6th Singapore Indie Doc Fest, 5-8.9.2013, the Substation, Singapore Panazorean International Film Festival, Azores, Portugal 11-20 April, 2013. 14th Jeonju International Film Festival JIFF, South Korea, 25.4-3.5.2013. Mubi, International Arthouse Cinema, online cinematheque, 2013 https://mubi.com/films/disappearing-landscape World Premiere: 42nd international Film Festival Rotterdam, Netherlands (world premiere)
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.099 | 0.015 |
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".