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Record W2990393593 · doi:10.1149/2.0731915jes

Flux: Software for Analysing SECM Data

2019· article· en· W2990393593 on OpenAlexafffund
Lisa I. Stephens, Janine Mauzeroll

Bibliographic record

VenueJournal of The Electrochemical Society · 2019
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsMcGill University
FundersNational Research Council Canada
KeywordsWorkflowPython (programming language)SoftwareScripting languageDisk formattingComputer scienceIntegratorFlux (metallurgy)Normalization (sociology)Computational scienceMaterials scienceElectrical engineeringVoltageProgramming languageOperating systemEngineeringDatabase

Abstract

fetched live from OpenAlex

Advancements in microelectrode fabrication, instrumentation, and theory have made data collection for scanning electrochemical microscopy (SECM) more accessible than ever before. In contrast, data treatment and analysis is still mostly done using proprietary or in-house tools or scripts. In this work, an open-source, free, Python-based software called Flux has been developed to treat SECM images, approach curves, cyclic voltammograms, and chronoamperograms. Flux provides a user-customizable data workflow that supports a range of common analyses including normalization of currents based on theoretical or experimental steady state currents, calculation of geometric (Rg), thermodynamic (formal potential), or kinetic (heterogeneous rate constant) parameters, and customizable plot formatting. Flux is compatible with standard output files from Biologic, CH Instruments, HEKA, and Sensolytics manufacturers.

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 score0.043
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.013
GPT teacher head0.262
Teacher spread0.249 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

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