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Record W107101100 · doi:10.2166/wqrj.2003.008

New Microcystin Concerns in the Lower Great Lakes

2003· article· en· W107101100 on OpenAlexaboutno aff
Tom Murphy, Kim Irvine, Jay Guo, John Davies, Henry R. Murkin, Murray N. Charlton, Susan B. Watson

Bibliographic record

VenueWater Quality Research Journal · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
FundersState University of New York
KeywordsMicrocystinMicrocystisAlgal bloomAlgaeHarbourBloomBiologyEcologyEnvironmental sciencePhytoplanktonMarine toxinEnvironmental chemistryNutrientCyanobacteriaToxinChemistryMicrobiology

Abstract

fetched live from OpenAlex

Abstract Water samples were collected in the summer of 2001 for microcystin analysis, nutrients and algal enumeration from Hamilton Harbour (Lake Ontario), Wendt Beach (Lake Erie) and Presque Isle (Lake Erie). Microcystin concentrations varied largely and were present at acute toxicity levels only in some wind-concentrated scums of blue-green algae (>90% Microcystis, primarily M. botrys, M. viridis and some M. wesenbergii) in Hamilton Harbour. In Hamilton Harbour, microcystin-RR was the main microcystin with microcystin-YR and -LR also present. The two samples of August 17 and September 7, taken during the peak of the cyanobacterial bloom, contained 60 and 400 μg/L, respectively. A few dying birds were seen in the Hamilton scums. The concentrations of microcystins at the Lake Erie sites were less than 1 μg/L, yet dead birds were common. The major limitation with this approach is that current analysis (ELISA and HPLC) methods are unable to measure covalently bound microcystins, the form that is assimilated into the food chain.

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 score0.100
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.099
GPT teacher head0.373
Teacher spread0.274 · 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

Citations83
Published2003
Admission routes1
Has abstractyes

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