MétaCan
Menu
Back to cohort
Record W4213321145 · doi:10.2166/wst.2021.640

Simplified validation of the ELISA kit determination of Microcystins in surface water

2021· article· en· W4213321145 on OpenAlexaff
Liang Fan, Jinhui Jeanne Huang‬‬‬‬, Ching Y. Lo, Bin Zhou, Xujin Fu

Bibliographic record

VenueWater Science & Technology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsToronto Metropolitan University
FundersMinistry of Science and Technology of the People's Republic of China
KeywordsMicrocystinChromatographyDetection limitReproducibilityChemistryStandard curveEnvironmental chemistryBiologyCyanobacteria

Abstract

fetched live from OpenAlex

The enzyme-linked immunosorbent assay (ELISA), as a universal method for the determination of Microcystins, is of great significance for the rapid detection of Microcystins pollution. This study aimed to propose a simplified validation method for Microcystins ELISA kit by summarizing related documents and guidelines. After summarizing and clarifying from 20 validation parameters, 11 parameters were selected to simplify the validation of Microcystins ELISA kit. In addition, the acceptable range and validation details of each parameter were analyzed. The results indicated that the coefficient of determination of the Microcystin-LR standard curve was higher than 0.99. The concentration of quality control samples was within control limits. The accuracy of spiked and proficient samples was within 70%-130%. The variability of intra-assay, inter-assay, and reproducibility was less than 11, 15 and 21%, respectively. The LOD and LLOQ were 0.002 μg/L and 0.05 μg/L, respectively. When the concentration of Microcystins exceeded 5 μg/L, it was recommended to dilute the samples to the working range before detection. The specificity was estimated with seven Microcystin analogues and three amino acids, indicating that the cross-reactivity was less than 30%. These results revealed that the ELISA kit was satisfactory for detecting Microcystins in water.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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 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

Citations14
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueWater Science & TechnologySame topicAquatic Ecosystems and Phytoplankton DynamicsFrench-language works237,207