Bibliographic record
Abstract
Se analiza el pretonema (los acentos prenucleares generados por el encadenamiento de niveles estaticos H(igh) y L(ow) a los segmentos). Se examinan acusticamente seis materiales de discurso espontaneo (los corpus DIES-RTVP) emitidos por dos hablantes masculinos (Bilbao y Cordoba, debates), por un hablante y una hablante (Madrid, locutores de radio), y por dos hablantes femeninos (Madrid, periodistas culturales). Los acentos tonales se clasifican segun microespacios determinados por diferencias psicofoneticas, el umbral tonal en cada acento gobierna la oposicion H contra L. Se indica una frecuencia de aparicion alta de acentos (H*, L+H*, (L+H*)+L) y una frecuencia de aparicion baja de acentos integrados por L*. Estos resultados son similares a los obtenidos en los discursos de Buenos Aires y en los discursos de Madrid (los corpus CREA). Los resultados no sostienen la idea de que los acentos prenucleares en los dialectos hispanicos son constantes (una ocurrencia de L*+H debido al overshooting), en cambio, lo contrario: la presencia de una taxonomia compleja.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".