Bibliographic record
Abstract
Quatre thèmes/numéros ont entrainé l’auteur vers une réflexion portée par des mots qui, tout naturellement, sont entrés en résonnance avec ses ancrages professionnels. Des mots qui sillonnent une mer riche d’aventures et d’ouvertures vers des contrées baignées de ce sens qui n’a de cesse de nourrir l’esprit des lieux au sein desquels, depuis la nuit des temps, l’architecture constitue une incontournable assise de l’histoire humaine. Les thèmes abordés sont :- Architectures des établissements d’enseignement supérieur (no 13) : des ancrages au cœur d’une urbanité en mouvement. - Émotions patrimoniales (no 17 & 22) : dans le respect de l’esprit des lieux. - Histoire du (des?) patrimoine (s) (no 33) : strate, stratigraphie, stratégie. - Le Phare et l’architecte (no 24) : balises inédites, éclairages innovants, amers prometteurs.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 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".