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Record W2157054272 · doi:10.1128/aem.00318-07

Molecular Characterization of Potential Microcystin-Producing Cyanobacteria in Lake Ontario Embayments and Nearshore Waters

2007· article· en· W2157054272 on OpenAlexaboutno aff
Amber M. Hotto, Michael F. Satchwell, Gregory L. Boyer

Bibliographic record

VenueApplied and Environmental Microbiology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
FundersNew York Sea Grant, State University of New YorkNational Oceanic and Atmospheric Administration
KeywordsMicrocystisMicrocystinBiologyCyanobacteriaGenotypeShoreBotanyEcologyFisheryGeneGeneticsBacteria

Abstract

fetched live from OpenAlex

The distribution and genotypic variation of potential microcystin (MC) producers along the southern and eastern shores of Lake Ontario in 2001 and 2003 were examined using a suite of PCR primers. Cyanobacterial, Microcystis sp., and Microcystis-specific toxin primer sets identified shoreline distribution of cyanobacterial DNA (in 97% of the stations) and MC synthetase genes (in 50% of the stations). Sequence analysis of a partial mcyA amplicon targeting Microcystis, Anabaena, and Planktothrix species indicated that the Microcystis sp. genotype was the dominant MC genotype present and revealed a novel Microcystis-like sequence containing a 6-bp insert. Analysis of the same samples with genus-specific mcyE primers confirmed that the Microcystis sp. genotype was the dominant potential MC producer. Genotype compositions within embayments were relatively homogenous compared to those for shoreline and tributary samples. MC concentrations along the shoreline exhibited both temporal and spatial differences as evidenced by the protein phosphatase inhibition assay, at times exceeding the World Health Organization guideline value for drinking water of 1.0 microg MC-LReq liter(-1). MC genotypes are widespread along the New York State shoreline of Lake Ontario, appear to originate nearshore, and can be carried through the lake via wind and surface water current patterns.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.565

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 studies0.0000.000
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 head0.002
GPT teacher head0.157
Teacher spread0.155 · 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

Citations67
Published2007
Admission routes1
Has abstractyes

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