Bibliographic record
Abstract
states, is a powerful, shadowy neo-noir pastiche that tracks the tightly wound central character, Teddy, an ex-soldier haunted by memories of his wife's accidental death-by-fire and his presence at the liberation of the Nazi concentration camp at Dachau, as he spirals into a world of madness and paranoia, in a film that is in the end itself framed by a semidark Calligarian misdirection -with a secret that indulges viewers long after that secret has been divulged.After reading the script, Robertson, who had previously collaborated with Scorsese as composer, producer, or consultant on a number of his films, including Raging Bull, The King of Comedy, Casino, and The Departed, was convinced that in order to add emotional texture to the film that didn't simply function as a cue to the action or to reinforce some plot point, but instead imparted a menacing and uncanny mood of suspense, tension and ambient unease, a soundtrack of mostly modern avant-garde classical pieces was necessary.Robertson, who for decades has been a fan of music residing outside the realm of popular culture -"music that…was never trendy, was never what's happening" (https://www.theringer.com
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".