Bibliographic record
Abstract
Au XIX e siècle, la littérature fantastique exploite le thème de la mort et devient une véritable littérature du cadavre. Dans des oeuvres telles que Frankenstein de Mary Shelley ou Le Rêve du docteur Mišić de K.S. Gjalski, les corps errent entre la vie et la mort et s’animent sous la plume des écrivains. Ces récits substituent le cadavre au traditionnel revenant et délaissent le surnaturel pour puiser l’horreur dans la réalité : le corps inerte y apparaît comme un objet de recherches scientifiques et fait du cimetière l’antichambre du laboratoire. À travers l’histoire du docteur Frankenstein et du docteur Mišić, le lecteur découvre la face sombre d’un siècle scientiste où la dépouille, devenue simple marchandise, se négocie et s’expose dans les salles de dissections. Les amphithéâtres des universités font ainsi de la mort un spectacle où les savants se prennent pour Dieu ; mais en défiant l’interdit et en brisant le tabou entourant le cadavre pour dévoiler les secrets de la nature, les héros fantastiques encourent un châtiment mortel.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.007 |
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".