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Record W2069821352 · doi:10.1139/cjm-47-11-994

Physical, chemical, and microbiological characteristics of microbial mats (KOPARA) in the South Pacific atolls of French Polynesia

2001· article· en· W2069821352 on OpenAlexvenueno aff
L. Mao, Serge Andréfouët, Virginie Bothorel, Muriel Guezennec, Hélène Rougeaux, Jean Guézennec, E. Deslandes, Jean Trichet, Robert Matheron, T. Le Campion, Claude Payri, Pierre Caumette

Bibliographic record

VenueCanadian Journal of Microbiology · 2001
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
Fundersnot available
KeywordsAtollBiologyPacific oceanGeographyEcologyOceanographyGeology

Abstract

fetched live from OpenAlex

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 (20-40 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 2-3 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.214
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2001
Admission routes1
Has abstractyes

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