Geographical isolation in hot spring cyanobacteria
Bibliographic record
Abstract
It has been proposed that free-living microorganisms exhibit ubiquitous dispersal, do not form geographically isolated populations and rarely (if ever) speciate via allopatry. We studied island-like hot spring cyanobacterial communities in which geographical isolation should be prominent and detectable if it influences the evolution of bacteria. The genetic diversity of cyanobacteria indigenous to North American, Japanese, New Zealand and Italian springs was surveyed by (i) amplification and cloning of 16S rRNA and 16S-23S internal transcribed spacer regions; (ii) lineage-specific oligonucleotide probing (used to verify the predominance of cloned sequences); and (iii) lineage-specific polymerase chain reaction (PCR) (used to search for possible rare genotypes). Phylogenetic and distribution patterns were found to be consistent with the occurrence of geographical isolation at both global and local spatial scales, although different cyanobacterial lineages were found to vary in their distribution. A lack of correspondence between biological patterning and the chemical character of springs sampled suggested that the geographical distribution of thermophilic cyanobacteria cannot be explained by the 20 potential niche-determining chemical parameters that we assayed. Thus, geographical isolation (i.e. genetic drift) must in part be responsible for driving the observed evolutionary divergences. Geographical isolation may be an important underestimated aspect of microbial evolution.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".