MétaCan
Menu
Back to cohort
Record W4399212400 · doi:10.28924/2291-8639-22-2024-92

Mathematical Modelling and Application of Analytical Methods for A Non-Linear EC2E Mechanism in Rotating Disk Electrode

2024· article· en· W4399212400 on OpenAlexvenueno aff
A. Nebiyal, R. Swaminathan, SG. Karpagavalli

Bibliographic record

VenueInternational Journal of Analysis and Applications · 2024
Typearticle
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMechanism (biology)MathematicsElectrodeMechanicsCalculus (dental)EpistemologyPhysicsChemistryPhysical chemistryOrthodontics

Abstract

fetched live from OpenAlex

Rotating disk electrode is the hydrodynamic technique used in the process of analyzing electroanalytic works. This paper deals with the mathematical model describing a non-linear EC2E mechanism that arises in a rotating disk electrode. This model is based on the system of non-linear reaction-convection-diffusion equations. EC2E mechanism has an application in finding the shape of current curves in the system of chronoamperometry in addition to steady-state voltammetry. The approximate analytical expression for the concentration of reactant species and current at steady-state condition is obtained using the analytical methods. The attained analytical result is compared with the numerical simulation (MATLAB) result. A satisfactory result is obtained between the series of solutions. The influence of parameters on the concentration of species and current is investigated and presented graphically.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.368
Teacher spread0.339 · 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 designSimulation or modeling
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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Analysis and ApplicationsSame topicSensor Technology and Measurement SystemsFrench-language works237,207