Bibliographic record
Abstract
Dreceres en l'aprenentatge morfofonèmicQuan els aprenents d'una llengua comencen a analitzar paraules morfològicament complexes, s'enfronten amb el problema d'obtenir les representacions subjacents a partir de les alternances morfofonèmiques que observen.La recerca sobre aprenentatge en teoria de l'optimitat ha començat a discutir aquest problema, i aquest article tracta sobre un dels aspectes.Quan les dades que presenten alternança indueixen l'aprenent a pensar que algunes formes [B] deriven de les formes subjacents /A/, l'aprenent podrà generalitzar, en determinades condicions, que totes les formes [B], fins i tot les que no presenten alternances, deriven de /A/.Una teoria adequada de l'aprenentatge ha d'incorporar, per tant, un mecanisme que permeti que les formes [B] que no presenten alternances agafin una drecera alternativa, de manera que puguin ser interpretades com una projecció no fidel /A/ → [B].
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.542 | 0.391 |
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".