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Record W2090021232 · doi:10.1039/c000966k

Temporal patterns and oscillatory voltage perturbation during an electrochemical process

2010· article· en· W2090021232 on OpenAlexaff
Saman Sadeghi, Michael Thompson

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2010
Typearticle
Languageen
FieldComputer Science
TopicNonlinear Dynamics and Pattern Formation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiological systemPerturbation (astronomy)ElectrolyteVoltageElectrochemistryOscillation (cell signaling)Chemical physicsChemistryComputer scienceControl theory (sociology)Materials sciencePhysicsElectrodeArtificial intelligenceControl (management)Physical chemistry

Abstract

fetched live from OpenAlex

The response of electrodissolution dynamics of nickel in sulfuric acid electrolyte was studied and categorized using efficient signal processing techniques. Time-frequency and phase analysis revealed complex dynamical patterns in anodic currents observed in the system. These patterns which respond to three-dimensional changes in the electrolyte and surface conditions, have a multitude of spatio-temporal properties which proved sensitive to oscillatory voltage perturbations, allowing signal recognition through distinct response patterns. Experimental work included studies on identification of control parameters, characterization of subsequent temporal patterns and examination of system response to information in the form of oscillatory voltage perturbations. Various data processing and pattern recognition techniques revealed the complexity and dynamics of these distinctive responses, which illustrate the capacity of the system to store information, with varying memory lengths. These patterns can be recalled upon excitation with particular perturbation cues.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.005
GPT teacher head0.227
Teacher spread0.221 · 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 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

Citations8
Published2010
Admission routes1
Has abstractyes

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