Genotypic composition and the relationship between genotypic composition and geographical proximity of the cyanobacterium <i>Microcystis aeruginosa</i> in western Japan
Bibliographic record
Abstract
Microcystis aeruginosa is one of the bloom-forming harmful algae in freshwater ecosystems. We genetically characterized Microcystis populations during bloom-forming periods in various reservoirs, lakes, and ponds in Japan during 2009. Using phylogenetic analysis, we evaluated the relationship between current genotype expansions and geographic location within western Japan and intraspecific variation. Microcystis aeruginosa colonies were isolated at 15 sites and were analyzed by sequencing the 16S-23S internal transcribed spacer (ITS) region of the ribosomal operon, and the potential to produce toxins was assessed by PCR-based detection of the microcystin synthetase gene mcyG. In total, 171 colonies were separated into 41 genotypes. The highest genotypic composition was detected in the south basin of Lake Biwa and the lowest in Lagoon Iba. Cluster analysis indicated no obvious association between genotypic composition and geographic distance. Thus, clear genetic differentiation accompanied by geographic origins was not found in western Japan. The resulting neighbor-joining tree revealed 3 clusters, 2 of which contained strains that showed both nonamplification and amplification of the mcyG gene.
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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 | 0.000 | 0.000 |
| 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 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".