Bibliographic record
Abstract
Dans cet article, j’aimerais démontrer comment des discours gréco-romains peuvent être élevés en armes au sein d’une société multiethnique particulière et empreinte de nombreux conflits religieux liés à des oppositions politiques récentes : la société de l’Empire romain du Ier siècle av. J.-C. au IVe siècle ap. J.-C. Il s’agit d’abord de présenter les débuts d’une bataille littéraire particulière, soit celle engageant les auteurs contre les cultes isiaques—branche du paganisme venant d’Égypte—en particulier lorsque l’Empire romain se développe suite à la victoire d’Octave sur Marc-Antoine et une certaine Cléopâtre… Il s’agit ensuite de démontrer l’évolution des attaques littéraires qu’ont subies les divinités isiaques, qui est parallèle à celle du statut officiel de l’isiasme et de la religion à Rome face à l’avancée du christianisme. Enfin, nous conclurons sur une (rare) réponse de la communauté isiaque du IVe siècle.
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 | 0.001 | 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 | 0.004 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".