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Microbialite genetic diversity and composition relate to environmental variables

2012· article· en· W1982612733 on OpenAlexaff
Carla M. Centeno, Pierre Legendre, Yislem Beltrán, Rocío Alcántara‐Hernández, Ulrika E. Lidström, Matthew N. Ashby, Luisa I. Falcón

Bibliographic record

VenueFEMS Microbiology Ecology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBiologyDiversity (politics)Composition (language)Genetic diversityEvolutionary biologyEcologyAnthropologyEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

Microbialites have played an important role in the early history of life on Earth. Their fossilized forms represent the oldest evidence of life on our planet dating back to 3500 Ma. Extant microbialites have been suggested to be highly productive and diverse communities with an evident role in the cycling of major elements, and in contributing to carbonate precipitation. Although their ecological and evolutionary importance has been recognized, the study of their genetic diversity is yet scanty. The main goal of this study was to analyse microbial genetic diversity of microbialites living in different types of environments throughout Mexico, including desert ponds, coastal lagoons and a crater-lake. We followed a pyrosequencing approach of hypervariable regions of the 16S rRNA gene. Results showed that microbialite communities were very diverse (H' = 6-7) and showed geographic variation in composition, as well as an environmental effect related to pH and conductivity, which together explained 33% of the genetic variation. All microbialites had similar proportions of major bacterial and archaeal phyla.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.008
GPT teacher head0.186
Teacher spread0.179 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations56
Published2012
Admission routes1
Has abstractyes

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