Bibliographic record
Abstract
El presente proyecto de grado se basa en el análisis de 3 referentes del Jazz: Daymé Arocena, Esperanza Spalding y Pat Metheny, cada uno desde un elemento musical específico, a fin de realizar un proceso de creación musical enfocado en 3 composiciones. Para el análisis musical de las obras de Daymé Arocena se explora todo el contenido melódico del tema “El 4, 5, 6” del álbum One Takes y de “Para el amor, cantar!” del álbum Sonocardiogram. En el caso de Esperanza Spalding se explora el elemento ritmo-melódico de los temas “She got to you” y “I know you know” de su álbum Esperanza. Por último, para el análisis de Pat Metheny se revisó todo el contenido armónico de los temas “Minuano” e “In her family” del álbum Still Life. Como producto creativo este proyecto se realizaron 3 composiciones basadas en 5 características generales de cada uno de los análisis. Durante el desarrollo de este escrito se encuentran investigaciones de temas como: El Jazz en sus inicios, el Jazz moderno, el latín Jazz, conceptos de armonía, melodía y ritmo-melodía, entre otros aspectos referentes a la temática del proyecto. Además, se encuentran entrevistas a artistas colombianas que fortalecen su objetivo principal.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.042 | 0.013 |
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".