MétaCan
Menu
Back to cohort
Record W4297919959 · doi:10.23977/jeeem.2022.050202

Determination of Furosemide Based on CdS QDs-Luc/MoSe2 Electroluminescent Detection Platform

2022· article· en· W4297919959 on OpenAlexvenueno aff
Xiaocan Chen, Qi Li

Bibliographic record

VenueJournal of Electrotechnology Electrical Engineering and Management · 2022
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsnot available
Fundersnot available
KeywordsDetection limitElectrochemiluminescenceElectroluminescenceMaterials scienceElectrodeLinear rangeCyclic voltammetryElectrochemistryAnalytical Chemistry (journal)Glassy carbonCarbon fibersNanotechnologyComposite numberChemistryChromatographyPhysical chemistryComposite material

Abstract

fetched live from OpenAlex

In this paper, a novel composite modified glassy carbon electrode (GCE) based on CdS QDs-Luc / MoSe<sub>2</sub> was constructed for the quantitative determination of furosemide by electroluminescence. The CdS QDs-Luc / MoSe<sub>2</sub> modified GCE was prepared by dropping 2 μL MoSe<sub>2</sub>, fluorescein (Luc) and CdS QDs solution to the glassy carbon electrode in turn. The electrochemical response characteristics of the sensor were characterized by electrochemiluminescence (ECL) and cyclic voltammetry (CV), and the preparation and detection conditions were optimized. The results show that the linear range of this method under the optimal conditions is 0.0 – 100 μM, and the linear equations are y= − 5822. 43x + 14475.94 (0.0 - 1.0 μM) and y = − 33. 60x + 8491.46 (1.0 - 100 μM), respectively. The correlation coefficients are R2 = 0.99465 and R2 = 0.99247, respectively. The new detection platform has the advantages of rapid response, high sensitivity, low detection limit, good stability and low cost, and has good application prospects.

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 score0.376
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.167
Teacher spread0.164 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Electrotechnology Electrical Engineering and ManagementSame topicElectrochemical sensors and biosensorsFrench-language works237,207