AMPER-Argentina: pretonemas en oraciones interrogativas absolutas
Bibliographic record
Abstract
Este trabajo es parte del Proyecto AMPER (Atlas Multimedia de la Prosodia del Espacio Románico). El área dialectal de estudio es el español de Buenos Aires. En el artículo se analizan las oraciones interrogativas absolutas SVO: un SN (núcleos sintácticos paroxítonos, proparoxítonos, oxítonos), un SV (núcleo paroxítono), un SPrep (núcleos paroxítonos, proparoxítonos, oxítonos). También se examinan los pretonemas según el modelo de entonación métrico y autosegmental (AM), y se observa la influencia de la frase fonológica (φ) en la representación fonológica de los acentos tonales. Los resultados de los pretonemas indican diferencias y no un único fraseo prosódico que caracterice a esta modalidad. Los primeros picos (P1) de la primera φ no muestran tonos más altos si se los compara con los P1 de oraciones declarativas. Se descarta un tono de frontera H% inicial. Estos hallazgos confirman otro estudio previo: la información sobre la modalidad interrogativa absoluta se encuentra fuera del pretonema, en el tonema final.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".