Bibliographic record
Abstract
CINEMA IS ABOUT creating images in motion. It reflects the essential denotation of an image as an optical reproduction of an object, scene, movement, gesture. It's about visual representations of our perceptions and ourselves. It's a medium through which directors project their visions, actors reincarnate themselves in ever new impersonations, and viewers watch the screen images as reflections of mimetic (or fantastic) reality. So far, it has been technology's greatest gift to the human imagination, a remarkable mirror of life-like illusions. Filmmakers naturally exploit cinema's fundamental reproductive nature, its inherent double-ness, often deliberately exploring questions of identity and reliability of our perceptions and judgements to engage us in fascinating games of visual deception and intellectual manipulation. Those themes typically involve mistaken identities, lookalikes, impostors, and alter egos, as well as incubi and body snatchers in their horror and sci-fi varieties. The protagonists live double (as in, say, Europa, Europa...
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.566 | 0.215 |
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".