Bibliographic record
Abstract
January 01 2020 More Liquid Than Solid Shoshanna White Shoshanna White Shoshanna White is an interdisciplinary artist currently based in New Mexico and Maine. Her practice includes photography, painting, and sculpture and public art installation, often informed by concerns of the environment. She has completed residencies in the United States, Canadian Maritimes and Norway. Search for other works by this author on: This Site Google Scholar Author and Article Information Shoshanna White Shoshanna White is an interdisciplinary artist currently based in New Mexico and Maine. Her practice includes photography, painting, and sculpture and public art installation, often informed by concerns of the environment. She has completed residencies in the United States, Canadian Maritimes and Norway. Online Issn: 1537-9477 Print Issn: 1520-281X © 2020 Shoshanna White2020Shoshanna White PAJ: A Journal of Performance and Art (2020) 42 (1 (124)): 24–26. https://doi.org/10.1162/pajj_a_00501 Cite Icon Cite Permissions Share Icon Share MailTo Twitter LinkedIn Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Shoshanna White; More Liquid Than Solid. PAJ: A Journal of Performance and Art 2020; 42 (1 (124)): 24–26. doi: https://doi.org/10.1162/pajj_a_00501 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsPAJ: A Journal of Performance and Art Search Advanced Search This content is only available as a PDF. © 2020 Shoshanna White2020Shoshanna White Article PDF first page preview Close Modal You do not currently have access to this content.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.551 | 0.200 |
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".