Bibliographic record
Abstract
TWO things are done after the arrest (which of them first is left up to the judge): the granting of arguments in defense and examination in the torture chamber (without the use of torture). The first is not granted unless she seeks it. The second is done only after the maids and associates, if she has any at home, are examined. Let us proceed in the order given here. If the accused woman says that she is innocent, that she has been falsely denounced, and that she would gladly|look at and hear her accusers, this is a sign that she is seeking arguments for defense. As to whether the judge is bound to make known to her those making depositions and to bring them into her presence, at this point the judge should note that he is obligated to do neither of these things, that is, make the names known or bring them into her presence, unless those giving depositions themselves voluntarily offer to do this, that is, be brought into their presence and to cast into the faces of the sorceresses the things about which they have given depositions. That the judge is not obliged to do this (because of the danger to those giving depositions) is proven as follows. Although various Supreme Pontiffs have given different pronouncements, none has ever given the pronouncement that a judge was obligated in such a case to make known to the accused the names of those giving depositions or of the accusers (though we are not using the proceeding by accusation). Rather, some held the opinion that this was not lawful in any situation, others that it was in some.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.094 | 0.022 |
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".