Edició del primer procés judicial per l’atac a Joan de Palomar (1426-1428)
Bibliographic record
Abstract
Es tracta de la instrucció de la cort del veguer de Barcelona per investigar el crim (per la llei Cornèlia de sicaris, la llei Júlia de lesa magestat i per sacrilegi) que haurien comès els germans Vidal, Narcís, sabater, Francesc, barber, i Pere, escuder del jurista i canonge Narcís de Sant Dionís. Se’ls acusa d’haver assaltat, colpejat i intentat assassinar el diaca i oïdor de comptes del General Joan de Palomar la nit de Nadal de 1426 a les rodalies de la Catedral de Santa Eulàlia, quan el clergue anava a assistir a Matines. Segons la instrucció, haurien comès el crim per a venjar l’honor del canonge Narcís de Sant Dionís, que a mitjan 1425 havia estat destituït del càrrec d’oïdor de comptes de la Diputació, després de ser-hi cooptat per al trienni de 1425-1428, però abans de jurar el càrrec, i havia estat substituït per Joan de Palomar. El crim va dur-se a terme per la complicitat del veguer de Girona, nebot de Sant Dionís, i homònim seu, qui va instigar un altre nebot del clergue, Bernat Sarriera, a organitzar l’atemptat.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".