Bibliographic record
Abstract
peripeties par OU Princesse est passee pour devenir Nejma, la prostituee, « celle qui a fornique avec les pauvres et les riches, les fous et les malades, les noirs et les blancs, les musulmans et les mecreants, les faibles et les puissants » (118).Soliman et Princesse, couple maudit, vont constituer, au cours de leurs peregrinations, une petite communaute qui tente d' echapper non seulement au controle de la police, mais aussi a 1'hypocrisie de la societe.Ce groupe errant se constitue peu a peu selon des affinites, comportant des noms celebres, meme si ce sont des declasses, tels que « rbn Roshd -alias Averroes -», « Chahine », alias Youssef Chahine, cineaste egyptien, « Casse-Cash, le boxeur », entralne par son ami Spielberg, cineaste americain, qui compte lui organiser un combat avec Mohammed Ali aux Etats-Unis.Mais cette dispute du.championnat du monde n'aura pas lieu.Elle restera dans le domaine du reve.Shakespeare devient « Cheikh Zoubeir », et Moliere « Cheikh Moliere.» Tant de permutations et de metamorphoses amusantes!Ce roman fluctue souvent entre le reel et le surreel, le vraisemblable et
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.030 | 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".