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Record W2086429896 · doi:10.1117/12.863131

Comparison of the microbial diversity and abundance between the freshwater land-locked lakes of Schirmacher Oasis, and the perennially ice-covered Lake Untersee in East Antarctica

2010· article· en· W2086429896 on OpenAlexfundno aff
Jonathan P. Huang, Richard B. Hoover, Ashit K. Swain, Chris Murdock, Dale T. Andersen, Asim K. Bej

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsnot available
FundersAlberta Agricultural Research InstituteTawani FoundationNational Aeronautics and Space Administration
KeywordsPhylumEcologyAbundance (ecology)Environmental scienceMicrobial population biologyMicroorganismCommunity structureGeographyBiologyBacteria

Abstract

fetched live from OpenAlex

Extreme conditions such as low temperature, dryness, and constant UV-radiation in terrestrial Antarctica are limiting factors to the survival of microbial populations. The objective of this study was to investigate the microbial diversity and enumeration between the open water lakes of Schirmacher Oasis and the permanently ice-covered Lake Untersee. The lakes in Schirmacher Oasis possessed an abundant and diverse group of microorganisms compared to Lake Untersee. Furthermore, the microbial diversity between two lakes in Schirmacher Oasis (Lake L27C and L47) was compared by culture-based molecular approach. It was determined that L27C had a richer microbial diversity representing 4 different phyla and 7 different genera. In contrast L47 consisted of 3 different phyla and 6 different genera. The difference in microbial community could be due to the wide range of pH between L27C (pH 9.1) and L47 (pH 5.7). Most of the microbes isolated from these lakes consisted of adaptive biological pigmentation. Characterization of the microbial community found in the freshwater lakes of East Antarctica is important because it gives a further glimpse into the adaptation and survival strategies found in extreme conditions.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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 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

Citations5
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicPolar Research and EcologyFrench-language works237,207