Bibliographic record
Abstract
The new Churchill Northern Studies Centre building was officially opened in August 2011. Its inaugural conference celebrated the thirty-year research legacy of Professor Bob Jefferies. Explore his, his students’ and colleagues’ research at Wapusk National Park and the Churchill area in the Robert Lenthall Jefferies Researcher Spotlight collection in Yorkspace. \nSince many delegates were returning to Churchill for the first time since they had done their field research here, they took the time to be tourists. \nHere we see the scene inside the popular local bakery, Gypsy’s Café. Sadly, it burned down in May, 2018 and an important local gathering spot was lost. \nYork University Professors Dawn Bazely (Biology) and Steve Alsop (Education) brought the Churchill Community of Knowledge Digital Archive back to Churchill in October 2019, including to the Duke of Marlborough School. Grade 5-9 students helped to describe this image and to create its Metadata. Their keywords were: RIP, fire, burning, very good food, arctic char and crispy donuts.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".