Bibliographic record
Abstract
De Tupelo (Mississippi), a Liverpool. De Seattle a Londres. De Toronto a Melbourne (Florida). De Baltimore (Maryland), a Cucamonga (California). De Duluth (Minessota), a Greenwich Village. De Chicago a Madrid. De Buenos Aires a Manchester. De Kingston (Jamaica), a Soweto. De Akron (Texas), a Athens (Georgia). De Gary (Indiana), a Ripley (Surrey). De San Francisco a Villefranche-Sur-Mer (Francia). De Bethel (Nueva York), al Altamont Speedway (California)… El mapamundi del rock sería muy parecido al que figura en la revista de a bordo de alguna aerolínea como United, American o Delta: una gran cantidad de puntos en Estados Unidos, bastantes en Canadá y Gran Bretaña, unos cuantos más en el resto del mundo. Pero una cosa es buscar en el mapa ciudades, pueblos, aldeas y barrios, o hasta hacer el peregrinaje respectivo, y otra imaginar cómo son esos vecindarios donde nacieron y crecieron los héroes, o donde el azar reunió a los que serían los futuros integrantes de alguna banda legendaria o esos sitios que le dan nombre a un movimiento amado u odiado: sonido de Munich, sonido de Filadelfia, movida madrileña…
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.008 |
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".