The Role of the Fecal Microbiome in Predicting Methane Emission in Cattle
Bibliographic record
Abstract
Six mature non-lactating Holstein dairy cows were offered one of three diets with forage to grain ratios of 100:0 (G0), 75:25 (G25), and 50:50 (G50). The forage portion of the diet consisted of 80% grass hay and 20% alfalfa hay (on a Dry Matter (DM) basis). The experiment was a replicated 3x3 Latin Square Design, each animal received each of the three diets over the course of the three 5-week periods. A statistical model was created combining 23 bacterial members in the feces, chosen due to their significant Variable Influence on Projection (VIP) values, along with ADF, NDF and starch formulated a basic predictive model for overall CH4 production (L d-1). The model had an R2 value of 0.51 and a Q2 value of 0.49. These 23 bacterial members, along with ADF, NDF, and starch can detect an increase or decrease from mean CH4 production levels.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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 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".