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Record W2353740802

Determination of NO_2~- and NO_3~- in Vegetable with Suppressed Ion Chromatography

2006· article· en· W2353740802 on OpenAlexaff
Guan Cui-lin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsDetection limitRelative standard deviationCorrelation coefficientChromatographyChemistryLinear correlationCoefficient of variationAnalytical Chemistry (journal)Standard deviationLinear rangeIonIon chromatographyLinear relationshipMathematicsStatisticsOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

NO~-_(2)and NO~-_(3) were determined with the method of suppressed ion chromatography.Under the optimum chromatographic conditions,NO~-_(2) and NO~-_(3) could be well separated within 8 min.For NO~-_(2),the detection limit was 0.002 mg/L,relative standard deviation was 2.58 %,liear range 0.2 mg/L~20 mg/L,correlation coefficient 0.999 6.For NO~-_(3),the detection limit was 0.011 mg/L,relative standard deviation was 2.01 %,linear range 0.3 mg/L~30 mg/L,correlation coefficient(0.999 2).This method was applied to determine NO~-_(2)and NO~-_(3) in vegetables with good result.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.716

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 head0.010
GPT teacher head0.193
Teacher spread0.183 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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