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Record W2154892350 · doi:10.1109/cic.2002.1166728

A multifractal inverse problem applied to heart rate data synthesis

2003· article· en· W2154892350 on OpenAlexafffund
D. C. Lin, J. Thevaril

Bibliographic record

VenueComputers in cardiology · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicComplex Systems and Time Series Analysis
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMultifractal systemMultiplicative functionStatistical physicsFractalScale invarianceGaussianPoisson distributionExponential functionMathematicsCascadeHeart rate variabilityMultiplicative noiseExponential distributionInverse Gaussian distributionInverseApplied mathematicsStatisticsMathematical analysisPhysicsComputer scienceDistribution (mathematics)Heart rateQuantum mechanicsEngineeringTelecommunicationsMedicine

Abstract

fetched live from OpenAlex

Daytime heart rate variability synthesis is proposed based on the assumption of multiplicative cascade. The parameters of the cascade were extracted from healthy RR intervals (RRi) to generate the synthetic data which reproduce some of the known HRV phenomenology, such as the multifractal scale invariance, stretch exponential-exponential-gaussian increment distribution transition from small to large increments, and Poisson excursion in small RRi fluctuation. However, this model only tackles the broad-band 1/f-like fractal component of HRV. Narrow-band components such as the respiration were not considered.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.001

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 head0.055
GPT teacher head0.234
Teacher spread0.179 · 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 designNot applicable
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

Citations2
Published2003
Admission routes2
Has abstractyes

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