Bibliographic record
Abstract
Berlin Remix is a computationally generative artwork that creates and presents a series of short films re-edited and re-mixed from the archetypal “City Film” documentary Berlin: Symphony of a Great City (Ruttman 1927). The “City Film” is an historical documentary genre. These City films thrived in the late 20s and 30s, and continue to this day. Each of them documented the daily life of an individual city. The central film in the development of this genre is Ruttman’s Berlin. Berlin Remix is a generative artwork that re-mixes the individual shots of the original film into a series of shorter films. Each of these shorter films differs from the others in specific content, cinematic style, or both. Each of the derived films shows a single facet or theme contained within the larger film. The final form of the artwork will run completely autonomously, generating the series of shorter films in real time. The artwork as exhibited at CSDH/SCHN 2019 required a moderate amount of human intervention to join the system’s output segments into short films. RésuméLe Berlin Remix est une oeuvre d’art informatiquement générative qui crée et présente une série de films courts remodifiés et remixés venant du documentaire de l’archétype « film de ville » (City Film) qui s’appelle Berlin : Symphony of a Great City (Ruttman 1927). Le « film de ville » est un genre documentaire historique. Ces films de ville s’épanouissaient pendant la fin des années 1920 et 1930, et aujourd’hui encore. Le film central du développement de ce genre est celui de Ruttman, nommé Berlin. Le Berlin Remix est une oeuvre d’art générative qui remixe les images individuelles du film original en série de films plus courts. Chacun de ces films plus courts varie l’un des autres selon le contexte spécifique, selon le style cinématographique, ou selon les deux à la fois. Chacun des films dérivés montre une facette ou un thème unique, confiné dans le film entier. La forme finale de cette oeuvre d’art fonctionnera de façon autonome, générant la série de films plus courts en temps réel. L’oeuvre d’art, comme exposé à CSDH/SCHN 2019, a exigé une quantité modérée d’intervention humaine afin de transformer la production de séquences du système en films courts. Mots clés: art vidéo; art générative; esthétics; cinématographique, filmdocumentaire; média numérique
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.051 | 0.006 |
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".