Bibliographic record
Abstract
La pratique photographique d’Aurélie Pétrel (1980) interroge le statut de l’image, son utilisation ainsi que les mécanismes de sa production. « Une prise de vue-souche ne vaut que par un mode d’existence ouvert et pluriel », déclare-t-elle. Formée à l’École des Beaux-Arts de Lyon, l’artiste enseigne au sein de la Haute École d’Art et de Design (HEAD – Genève, HES-SO) depuis 2012 et codirige le Laboratoire d’expérimentation du Collège international de Photographie du Grand Paris. Ses oeuvres ont été exposées en France (Lyon, Paris, SaintÉtienne), comme à l’international (Toronto, New York, Genève, Portugal). Aurélie Pétrel a également participé à plusieurs résidences (Cité internationale des arts, Institut français & Gallery 44 Center for Contemporary Photography à Toronto, ou encore la Villa Kujoyama, Institut français, à Kyoto)
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.104 | 0.027 |
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".