Consistent spatial patterns in microbial taxa of red squirrel gut microbiomes
Bibliographic record
Abstract
Gut microbiomes are diverse ecosystems whose drivers of variation remain largely unknown, especially in time and space. We analysed a dataset with over 900 red squirrel (Tamiasciurus hudsonicus) gut microbiome samples to identify the drivers of gut microbiome composition in this territorial rodent. The large-scale spatiotemporal replication in the data analysed was an essential component of understanding the assembly of these microbial communities. We identified that the spatial location of the sampled squirrels in their local environment is a key contributor to gut microbial community composition. The non-core gut microbiome (present in less than 75% of gut microbiome samples) had highly localised spatial patterns throughout different seasons and different study areas in the host squirrel population. The core gut microbiome, on the other hand, showed some spatial patterns, though fewer than in the non-core gut microbiome. Environmental transmission of microbiota is the likely contributor to the spatiotemporal distribution observed in the North American red squirrel gut microbiome.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".