Quilts 4 Cancer: Quilt block inspiration and evaluation tools
Bibliographic record
Abstract
Quilts 4 Cancer is a public engagement with research project funded by the Royal Society of Chemistry. The project was the brainchild of Dr Clare Hoskins and Dr Kirsty Ross, both of the Department of Pure & Applied Chemistry at the University of Strathclyde. The aim of the project was threefold: 1) Support and enable researchers to share their research through the medium of quilt block design inspiration.2) Raise awareness of cutting edge chemical research into pancreatic cancer amongst quilters by inspiring them to create quilts based on the researcher's designs.3) Donate created quilts to patients with pancreatic cancer around Glasgow and beyond to keep them warm during their treatments. We received 16 completed quilts at the end of the project, blasting past our target of 6! One is even on it's way to Saskatchewan, Canada. The files attached here include: * Quilts 4 Cancer: Quilt pattern inspiration * Pre- and post-event evaluation card* Thoughts about Quilts 4 Cancer evaluation card for participants
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 | 0.025 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.080 | 0.016 |
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".