Max Seckler, éd., Aux origines de l’École de Tübingen. Johann Sebastian Drey, Brève introduction à l’étude de la théologie (1819). Présentation et introduction par Max Seckler, traduction par Joseph Hoffmann, avec des contributions du cardinal Joseph Ratzinger, du cardinal Walter Kasper et de Max Seckler, ainsi que des textes de P. Chaillet, M.-D. Chenu, Y. Congar et P. Godet, postface de M Joseph Doré. Paris, Les Éditions du Cerf (coll. « Patrimoines », série « Christianisme »), 2007, 398 p.
Bibliographic record
Abstract
Max Seckler, éd., Aux origines de l’École de Tübingen. Johann Sebastian Drey, Brève introduction à l’étude de la théologie (1819). Présentation et introduction par Max Seckler, traduction par Joseph Hoffmann, avec des contributions du cardinal Joseph Ratzinger, du cardinal Walter Kasper et de Max Seckler, ainsi que des textes de P. Chaillet, M.-D. Chenu, Y. Congar et P. Godet, postface de Mgr Joseph Doré. Paris, Les Éditions du Cerf (coll. « Patrimoines », série « Christianisme »), 2007, 398 p.. Un article de la revue Laval théologique et philosophique (Volume 64, numéro 2, 2008, p. 233-575) diffusée par la plateforme Érudit.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.058 | 0.031 |
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".