Frontiers in ruminant nutrition: An ASAS-CSAS-WSASAS 2020 Symposium overview
Bibliographic record
Abstract
The Frontiers in Ruminant Nutrition Symposium was recently held at the 2020 joint American Society of Animal Science (ASAS), Canadian Society of Animal Science (CSAS), and Western Section of the American Society of Animal Science (WSASAS) in virtual format. This symposium was designed to showcase specific areas of ruminant nutrition research that represent current and emerging research frontiers. The purpose of the symposium was to stimulate discussion, creative research, and scholarship activities within these critical areas through relevant presentations by leading scientists in specifically selected fields. Five presentations were selected for this year’s “Frontiers in Ruminant Nutrition” symposium. The first was the 2020 American Feed Ingredient Association Ruminant Nutrition Award recipient presentation by Dr. Terry Engle (Engle, 2020), who presented “Effect of Trace Mineral Source on Rumen Fermentation and Trace Mineral Distribution in the Rumen.” The second presentation was entitled “Micronutrients, One-Carbon Metabolism, and Epigenetics: Potential Developmental and Production Outcomes” was provided by Dr. Matthew Crouse (Crouse et al., 2020a). The third presentation was given by Drs. Shawn Archibeque, Jasmine Dillon, and Kristen Johnson (Archibeque et al., 2020) and focused on “Linking Nutrition, Production, and Environmental Aspects of Ruminant Livestock Production.” Dr. T. G. Nagaraja (Nagaraja, 2020) gave the fourth presentation on “Nutrition and the Ruminal Microbiome: Emerging Frontiers from an Old Friend.”. The final presentation was entitled “Past, Present and Future of Protein and N Metabolism in Ruminants” and was presented by Drs. Gerald Huntington and Joan Eisemann (Huntington and Eisemann, 2020).
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.014 |
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".