VII Jornada REALITER sobre "Multilingüisme i prà ctiques terminològiques" (Quebec juny 2011)
Bibliographic record
Abstract
Vol. 34 (2012), p. 669-728 CRÒNICA 719 Joan Veny, per tant, no té, únicament, la tasca d'anar enllestint, cada dos anys, un nou volum de l'Atles, que ja n'hi hauria prou per estar-ne ben contents i agraïts.A més, sabem que, a part de moltes altres qualitats, és un home feiner.Per això mateix, a l'abril d'enguany, apareixia el volum XXXIII d'aquesta revista, a cura d'Antoni M. Badia i Margarit i Joan Veny, on hi poguérem llegir el treball del filòleg campaner: Sobre derivats populars catalans del gerundiu (p.293-302); i també dues recensions de llibres seus: la de Joan Miralles sobre Estudis lingüístics valencians (Joan Veny, 2009) i la de Pere Navarro que dissertava sobre Scripta eivissenca (Joan Veny / Àngels Massip, 2009).Constatem, finalment, l'admiració i agraïment a tots aquells que, com Veny i Lídia Pons, han contribuït a lliurar-nos -a hores d'ara-aquests cinc primers volums de l'Atles Lingüístic del Domini Català, que guardarem -amb els que aniran arribant-com el tresor més estimat dins el cofre dels mots i dels sons.Amb els seus significats, com a pont i eina per entendre'ns millor, i perquè, en definitiva: què seria de la vida sense la bellesa que les paraules dibuixen?
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
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".