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Detection of microcystins using electrospray ionization high-field asymmetric waveform ion mobility mass spectrometry/mass spectrometry

2000· article· en· W2007220030 on OpenAlexaff
Barbara Ells, Kenneth L. Froese, Steve E. Hrudey, Randy W. Purves, Roger Guevremont, David A. Barnett

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsNational Research Council CanadaSciex (Canada)University of Alberta
FundersAmerican Water Works Association Research FoundationWater Research Foundation
KeywordsChemistryIon-mobility spectrometryMass spectrometryIon-mobility spectrometry–mass spectrometryElectrospray ionizationDirect electron ionization liquid chromatography–mass spectrometry interfaceChromatographyAnalytical Chemistry (journal)Thermal ionization mass spectrometryElectrosprayExtractive electrospray ionizationIonSample preparation in mass spectrometryIonizationChemical ionization

Abstract

fetched live from OpenAlex

A combination of electrospray ionization, high-field asymmetric waveform ion mobility spectrometry, and mass spectrometry (ESI-FAIMS/MS) was used to analyze standard solutions of microcystins-LR, -RR, and -YR. The ability of FAIMS to separate ions in the gas phase reduced the amount of background in the mass spectrum without compromising the absolute signal for these microcystins. This reduction in background resulted in a ten-fold improvement in the signal-to-background ratio over conventional ESI-MS. Detection limits, using direct infusion, were determined to be 4, 2, and 1 nM for microcystins-LR, -RR, and -YR, respectively.

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)0.002
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.009
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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.

Study designBench or experimental
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

Citations40
Published2000
Admission routes1
Has abstractyes

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