Termite Hindguts and the Ecology of Microbial Communities in the Sequencing Age
Bibliographic record
Abstract
Advances in high-throughput nucleic acid sequencing have improved our understanding of microbial communities in a number of ways. Deeper sequence coverage provides the means to assess diversity at the resolution necessary to recover ecological and biogeographic patterns, and at the same time single-cell genomics provides detailed information about the interactions between members of a microbial community. Given the vastness and complexity of microbial ecosystems, such analyses remain challenging for most environments, so greater insight can also be drawn from analysing less dynamic ecosystems. Here, we outline the advantages of one such environment, the wood-digesting hindgut communities of termites and cockroaches, and how it is a model to examine and compare both protist and bacterial communities. Beyond the analysis of diversity, our understanding of protist community ecology will depend on using statistically sound sampling regimes at biologically relevant scales, transitioning from discovery-based to experimental ecology, incorporating single-cell microbiology and other data sources, and continued development of analytical tools.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 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 teacher head, 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".