Why this work is in the frame
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Bibliographic record
Abstract
The present paper proposes a cognitive view on prominence relations of utterances by treating them as prosodic relations with weak-strong metrical structure. Considering this aspect, prosodic relations have a cognitive structure and a prominence structure, both of them reflecting the structures of cognitive relations generated at cortical level during the evocation of auditory objects corresponding to speech constituents. Ladd (2008) introduces two types of relations in the F0 contour description, prosodic and prominence relations, but we suggest a single type of relation between speech constituents, named prosodic relation, and consider it is in the same time a prominence relation due to its weak-strong metrical structure. In section 2, the paper presents the cognitive model of information structure by defining the categories used for the description of cognitive and prominence structures of prosodic relations. In section 3, the cognitive and prominence structures of four utterances of the word permit as noun and verb, in descending and ascending F0 contours, are compared with those of four utterances of certain small statements and questions having words as constituents. All the contours mentioned are useful for understanding how utterances can be decomposed into binary hierarchies of prosodic relations with local or global prominent (strong) constituent, aiming to motivate researchers to take into account the cognitive interpretation of F0 contours.
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.
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 | 0.002 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it