Yukon Winter Tick Monitoring: Government of Yukon cervid hide harvest submissions 2011 - 2020
Bibliographic record
Abstract
Data associated with Chenery et al., 2022. Improving widescale monitoring of ectoparasite presence in northern Canadian wildlife with the aid of citizen science. See also ReadMe worksheet of dataset for full metadata. Records of harvested hides (animal skins) of moose, elk, caribou and mule deer from Yukon, Canada, submitted to the Government of Yukon between 2011-2020. Hides and hide samples were checked for presence of the winter tick, Dermacentor albipictus, using a hair transect method (described in Chenery et al., 2022) and the number of ticks present recorded, along with the harvest date, sex, species and locality of kill (game management subzone). Associated data relating to assessing hunter engagement with a citizen science program, the Yukon Winter Tick Monitoring Project (YWTMP) (2018-2020) are also included. These describe the level of conformity with YWTMP sample kit instructions (size of hide sample provided, information completed), and are discussed more fully in the associated manuscript.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 0.021 |
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".