Determination of Microbial Communities beneath Livestock Burial Sites
Bibliographic record
Abstract
A ten year old livestock burial site near Pierceland, Saskatchewan was continuously cored and analyzed for microbial communities at varying depths below the soil surface by molecular methods. 16S rRNA gene targets and quantitative PCR was utilized to provide a quantitative analysis of genomes per gram of soil and cpn-60 targets were used to amplify DNA for taxonomic profiling by 454 pyrosequencing. Quantification results demonstrate a three orders of magnitude greater difference in genomes at depths within and up to two meters below the burial trench as compared to a background core. Topsoil and depths below 6 meters show similar quantities of microbes for both the core through the burial trench and the background core. A total of 5905 OTUs was found at a variety of abundances in all of the 13 core samples that were analyzed. Taxonomic analysis indicated that the overall community composition changed considerably with increasing depth, and that the burial core community was distinct from the control core at the same depth. In the burial core, organisms that are associated with phosphate accumulation, nitrogen fixation, and ammonium oxidation were found in highest abundance near the surface (up to 2.5 m), while organisms associated with sulfate reduction were concentrated just below the burial depth (4.5-4.8 m). The microbial community at the burial site (3.75 m) was dominated by anaerobic microorganisms.
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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 | 0.000 |
| 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".