Bibliographic record
Abstract
Obra de David Mamet dirigida per Pep Anton Gómez. Traducció: Pilar Alba i Sergi Belbel. Intèrprets: Ione Avila: Dona d'Edmond; Anna Bertran: Tafurer, dependenta casa préstecs, policia, capellà; Pol Cardona: Edmond 5; Meritxell Díaz: Pitonissa, madam, dona metro; Robert Donaldson: Edmond 2; Anna Flavià: Transeünt, recepcionista, predicador; Laia Gausà: Noia peep-show, inspector; Mariona Ibañez: Glenna; Ton Mansilla: Edmond 1; Daniel Masalles: Edmond 4; Judit Naranjo: Noia barra, clienta casa préstecs; Paula Rodríguez: Puta, dependenta casa préstecs; Adrià Rodríguez: Edmond 3; Joan Sentís: Home bar, còmplice, presoner; Thibaut Sentis: Còmplice; Vignesh T. Melwani: Cambrer, macarra, policia. Il·luminació: Jaume Ventura (Stem); Espai sonor: Pere Hernàndez; Fotografia i assistent direcció: Thibaut Sentis; Coordinació escenografia i utilleria: Joan Sentís i Thibaut Sentís; Coordinació vestuari: Paula Rodríguez; Disseny gràfic: Robert Donaldson; Realització audiovisual: Arcade Productions. Producció: Aula de Teatre de la Universitat Pompeu Fabra
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.044 |
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; both teacher heads agree on what is shown here.
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".