Bibliographic record
Abstract
Varela & Martin Garcia(1999) describe that in Spanish some prefixes change the syntactic projection of the argument of the simple predicate (El clavo ha pasado por la pared > El clavo ha traspasado la pared. El piloto vuela sobre el lago Ontario > El piloto sobrevuela el lago Ontario), and through this kind of prefixation, the optional complement of the sentence like Sacaron las bolas negras (de entre las blancas) is converted as the obligatory complement of the complex predicate in Entresacaron las bolas negras *(de entre las blancas). In the sentence Entresacaron las bolas negras *(de entre las blancas), we can observe that the Path prepositional prefix has the same phonetic feature with the Path Preposition. This kind of phenomena can also be observed in the sentences like El rio afluye al mar, Un pajaro sobrevuela sobre la estatua de la libertad durante la puesta de sol en Nueva York. In this article, we provide a morpho-syntactic account, within the framework of Distributed Morphology(cf. Halle & Marantz(1993)) to show that the simultaneous realization of Path Prefix and Path Preposition with the same phonetic feature is closely related to the spell-out condition in the derivational confuguration with respect to the Path feature.
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 | 0.001 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".