Bibliographic record
Abstract
La Disparition de Perec ne cesse de désigner son principe constitutif, l'omission de la lettre E . Le danger de répétition est grand pour un récit qui ressasse l'impossibilité de nommer ce qui est par définition indicible. D'où le besoin de diversifier le sytème autoreprésentatif. L'emprunt (citation de lipogrammes préexistants, lipogramme de citation et réduction lipogrammatique de volumes entiers) relance la contrainte générative en lui soumettant de nouveaux matériaux à transformer et à intégrer. Les emprunts individuels se chargent de significations nouvelles, des liens se forgent entre des textes qui semblaient n'avoir rien de commun, et les grands symboles de l'histoire littéraire, tel Moby Dick, sont traités littéralement. La symbolique du signe absent peu à peu s'enrichit, et le comique y gagne.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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; both teacher heads agree on what is shown here.
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".