Development and Implementation of a Mandatory Animal Identification System: The Canadian Experience
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article provides a brief history of the animal identification (ID) system that previously existed in Canada along with details on efforts to “reidentify” the country's cattle herd. The current state of ID for various species is summarized, and the state of regulations federally and for major agricultural province are outlined. A short background on the economics of animal ID is provided. Particular attention is paid to the operation of the Canadian Cattle Identification Agency, an industry-government initiative charged with identifying the national cattle herd. The animal ID system in Canada is found to have performed well when called on in times of animal health crises, although there have been notable deficiencies in its performance on occasion. Canada's animal ID system will continue to evolve as new technologies for tagging and database management (among others) are developed. It is expected the system will play an important role in future attempts to exploit traceability for value-added initiatives.
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.
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 | 0.000 |
| 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) | 0.000 | 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 it