Particules (correspondances inattendues) 2022: internet végétal
Bibliographic record
Abstract
Particules est une performance annuelle organisée en partenariat par le Mouvement Art Mobile et Littérature Québécoise Mobile. En 2021, elle a été accompagnée par la communauté interdisciplinaire de Rhizome, l’équipe de La Traversée et la Maison des arts littéraires. Lors de chaque édition, des artistes visuels et des écrivain.e.s professionnel.le.s sont invité.e.s à publier des tweets sur une thématique donnée, en mettant leurs gazouillis en réseau par l’utilisation d’un même mot-clic. Puisque les publications sont instantanément disponibles, des conversations se créent. Le mot-clic fédère ainsi les auteur.rice.s et constitue une anthologie mouvante de tweets poétiques, textuels, iconiques ou iconographiques. L’ouverture de la performance au grand public permet également de recueillir les gazouillis d’internautes qui n’ont pas nécessairement une pratique artistique professionnelle. L’expérience artistique est alors partagée : les publications amateures et celles d’artistes chevronné.e.s apparaissent sans hiérarchie, s’imbriquant et se mêlant en conversations inattendues.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 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".