Physical, chemical, and microbiological characteristics of microbial mats (KOPARA) in the South Pacific atolls of French Polynesia
Bibliographic record
Abstract
Microbial mats that develop in shallow brackish and hyposaline ponds in the rims of two French polynesian atolls (Rangiroa and Tetiaroa) were intensively investigated during the past three years. Comparative assessment of these mats (called kopara in polynesian language) showed remarkable similarities in their composition and structure. Due to the lack of iron, the color of the cyanobacterial pigments produced remained visible through the entire depth of the mats (2040 cm depth), with alternate green, purple, and pink layers. Profiles of oxygen, sulfide, pH, and redox showed the anoxia of all mats from a depth of 23 mm. Analyses of bacterial pigments and bacterial lipids showed that all mats consisted of stratified layers of cyanobacteria (mainly Phormidium, Schizothrix, Scytonema) and purple and green phototrophic bacteria. The purple and green phototrophic bacteria cohabit with sulfate reducers (Desulfovibrio and Desulfobacter) and other heterotrophic bacteria. The microscopic bacterial determination emphasized the influence of salinity on the bacterial diversity, with higher diversity at low salinity, mainly for purple nonsulfur bacteria. Analyses of organic material and of exopolymers were also undertaken. Difference and similarities between mats from geomorphological, microbiological, and chemical points of view are discussed to provide multicriteria of classification of mats.Key words: microbial mats, cyanobacteria, bacterial pigments, French Polynesia atolls, exopolymers.
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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 | 0.001 |
| 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".