Bibliographic record
Abstract
[Full text PDF link below] About the Artist Stephanie Ryan is a watercolour artist living in Whitehorse, Yukon. Originally from Sydenham, Ontario, Stephanie fi rst travelled west in 1994 as a tree planter in northern BC. She completed her BA in Environmental & Natural Resource Studies at Trent University, and ventured further north to the Yukon in 1997. She has worked as a landscaper and garden designer, and more recently as a backcountry patroller on the Chilkoot Trail. The wild rivers and mountainsides are inspiring for her art and spirit. Her winters are spent painting in her studio and skiing in the local mountains. Her paintings each feature a bit of the sense of awe she feels when she is in the mountains, on some great river, or in a beautiful backyard garden. Stephanie’s work has been commissioned by various groups, including Yukon Brewing, Coast Mountain Sports, and the City of Whitehorse. Her work has also been featured with international publications in Germany, the United Kingdom, and Japan. She is a member of the Yukon Artists at Work co-operative, and also exhibits at the North End Gallery (Whitehorse) and Alaska Artworks (Skagway). Artist’s Statement I fi nd that my best work comes from being immersed in a natural sett ing, when all other distractions fall away and I am left to just take in my surroundings. Sketching beside a river or up a mountainside off ers an inspiring perspective, where the continual changes in light, weather, and trip events provide a really unique sett ing for making art. I like to simplify what I see, focusing in on what has caught my att ention. I use watercolour because I love its portability and the ease with which one can mix colours and apply them. As I set out my lines, I am developing paintings that I hope will capture my experiences and connect other people to that same sense of joy and awe I felt.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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; both teacher heads agree on what is shown here.
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".