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Record W2990080654 · doi:10.5539/jmr.v11n6p70

Effect of Mixed Spikes on Different Types of Complex Waves

2019· article· en· W2990080654 on OpenAlexvenueno aff
A.N.M. Rezaul Karim

Bibliographic record

VenueJournal of Mathematics Research · 2019
Typearticle
Languageen
FieldComputer Science
TopicBlind Source Separation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMathematicsRepresentation (politics)Series (stratigraphy)MATLABVariable (mathematics)Spike (software development)Power (physics)Domain (mathematical analysis)Order (exchange)Statistical physicsMathematical analysisComputer scienceThermodynamicsPhysics

Abstract

fetched live from OpenAlex

This article treats analytically. This paper presents a novel approach to complex waves. This article outlines the understanding of the various effects of spike representations used to make models of the predictive variable effects of the second-order portion of power while revealing the relationship between the time series segments that are recorded from a single unit. MATLAB has been used to show the effects of mixed spikes in graphs. The resulting power portion has varied representation effects in which both the random and fixed effects are expressed as functions of the frequency domain.

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)0.004
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 score0.423
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 science0.0010.000
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 head0.087
GPT teacher head0.416
Teacher spread0.329 · 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
Published2019
Admission routes1
Has abstractyes

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