Bibliographic record
Abstract
Environmental issues have expanded to the forefront of livestock production systems. Air and water quality, human health concerns, and pathogens associated with manure are important issues being examined in swine production systems. In addition, methodologies to reduce or eliminate these issues have become important avenues of scientific research. These topics were the focus of the Swine Symposium on Environmental Concerns Based on Swine Production held at the joint annual meeting of the American Society of Animal Science, American Dairy Science Association, and the Canadian Society of Animal Science in Montréal, Québec, Canada, July 12 to 16, 2009. An introduction to the symposium, provided by D. J. Meisinger, executive director of the US Pork Center of Excellence (USPCE) located in Ames, Iowa, summarized 2 invitational workshops designed to develop research and extension needs in air and water quality (Meisinger, 2009). Discussions among experts at these workshops, hosted by the USPCE and the Environmental Committee of the National Pork Board (Des Moines, IA), resulted in the identification of producer materials that should be developed based on available research, a recommended list for development of producer educational and informational materials based on available research, identification of research efforts needed to fill gaps in information, and a recommended priority list for identified research needs (USPCE, 2009).
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 | 0.000 |
| 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 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".