Bibliographic record
Abstract
Colour Constructs / Constructions en couleursRodman Hall (30 Nov. 2017-4 March 2018)In fall 2017, Rodman Hall invites visitors to experience the exhibition Material Girls, which brings together Canadian and international female artists from across artistic disciplines and cultural backgrounds. Giving particular attention to the colourfulness and jubilance of this exhibition, in Colour Constructs, students in Visual Arts, Studies in Arts and Culture, and French Studies explore the materiality of colours in their own diverse ways. Student works are complemented by graffiti art by Niagara-based artist Mat Vizbulis, a classroom guest during the semester.A l’automne 2017, Rodman Hall invite ses visiteurs à l’exposition Material Girls, qui rassemble des femmes artistes canadiennes et internationales de diverses disciplines et cultures. Prêtant une attention particulière aux couleurs jubilantes de cette exposition, des étudiants d’Arts visuels, d’Etudes en arts et culture et d’Etudes en français explorent dans Constructions en couleurs la matérialité des couleurs. Leurs travaux sont accompagnés d’art graffiti de l’artiste Mat Vizbulis, basé dans la région du Niagara et un intervenant en cours pendant le semestre.Curators / Commissaires d’exposition: Catherine Parayre and Shawn Serfas
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".