Bibliographic record
Abstract
Abstract Bison (Bison bison) are a majestic species native to North America that have a rich yet turbulent history. This iconic species is valued due to its cultural significance among indigenous people, impact on the vast geography that it inhabited and commercially for its meat products with desirable attributes. Conservation efforts have included both public and privately owned herds, and efforts to increase their numbers presently continue on both fronts. The objective of this presentation is to provide some historical context about bison, an overview of bison ranching in North America, review research on bison and suggest research topics of importance for this species. Bison roamed North America from Alaska to the northern tier of Mexican states in massive numbers up until the late 1800’s where relentless hunting and waste dwindled their numbers to no more than 1500 head. Today the farmed bison industry in North America is a thriving livestock industry with over 300,000 bison on farms and a keen consumer interested in the story and sustainability of bison. The primary product from the industry is meat, but skulls, hides and farm tourism are also sources of revenue for the industry. There is much about bison that is unknown, but the body of knowledge is increasing as research is published and through code of practice development. Genetic testing and disease surveillance are important tools for species preservation, both on private ranches and public herds. Understanding bison seasonality, adaptations to low quality forages, interactions with their environment and sensitivity to stress helps both the conservation and commercial raising of bison. More research into nutrition, meat quality, reproduction, technology adoption and handling techniques to lower impacts of stress will help efforts towards successfully raising and enjoying bison.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 0.005 |
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".