Phylogenetic analysis of methanogens from the bovine rumen
Bibliographic record
Abstract
BACKGROUND: Interest in methanogens from ruminants has resulted from the role of methane in global warming and from the fact that cattle typically lose 6 % of ingested energy as methane. Several species of methanogens have been isolated from ruminants. However they are difficult to culture, few have been consistently found in high numbers, and it is likely that major species of rumen methanogens are yet to be identified. RESULTS: Total DNA from clarified bovine rumen fluid was amplified using primers specific for Archaeal 16S rRNA gene sequences (rDNA). Phylogenetic analysis of 41 rDNA sequences identified three clusters of methanogens. The largest cluster contained two distinct subclusters with rDNA sequences similar to Methanobrevibacter ruminantium 16S rDNA. A second cluster contained sequences related to 16S rDNA from Methanosphaera stadtmanae, an organism not previously described in the rumen. The third cluster contained rDNA sequences that may form a novel group of rumen methanogens. CONCLUSIONS: The current set of 16S rRNA hybridization probes targeting methanogenic Archaea does not cover the phylogenetic diversity present in the rumen and possibly other gastro-intestinal tract environments. New probes and quantitative PCR assays are needed to determine the distribution of the newly identified methanogen clusters in rumen microbial communities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".