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Record W1996331891 · doi:10.1016/j.femsec.2004.11.001

Extremotrophs, extremophiles and broadband pigmentation strategies in a high arctic ice shelf ecosystem

2004· article· en· W1996331891 on OpenAlexafffundabout
Derek Mueller, Warwick F. Vincent, Sylvia Bonilla, Isabelle Laurion

Bibliographic record

VenueFEMS Microbiology Ecology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité LavalCenter for Northern Studies
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyExtremophileEcosystemAutotrophExtreme environmentArcticOceanographyPsychrophileHeterotrophIrradianceSalinityEcologyMicroorganismBacteria

Abstract

fetched live from OpenAlex

Remnant ice shelves along the northern coast of Ellesmere Island, Nunavut, Canada ( approximately 83 degrees N) provide a habitat for cryo-tolerant microbial mat communities. Bioassays of bacterial and primary production were undertaken to quantify the short-term physiological response of the mats to changes in key variables that characterize this cryo-ecosystem (salinity, irradiance and temperature). The heterotrophic versus autotrophic community responses to these stressors differed markedly. The heterotrophic bacteria were extremophilic and specifically adapted to ambient conditions on the ice shelf, whereas the autotrophic community had broader tolerance ranges and optima outside the ambient range. This latter, extremotrophic response may be partly due to a diverse suite of pigments including oligosaccharide mycosporine-like amino acids, scytonemins, carotenoids, phycobiliproteins and chlorophylls that absorb from the near UV-B to red wavelengths. These pigments provide a comprehensive broadband strategy for coping with the multiple stressors of high irradiance, variable salinity and low temperatures in this extreme cryo-environment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.080
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations131
Published2004
Admission routes3
Has abstractyes

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