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Wavelet Based Fractal Analysis of Airborne Pollen

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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M.E. Degaudenzi, C.M. Arizmendi

adap-org · Submitted 27 Aug 1998

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The information and the correlation dimensions correspond to a chaotic system showing loss of information with time evolution.

how it is stated · asserted 1.00 read the record →

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arXiv IDadap-org/9808004 (version 1)
Pith IDDN6DQRXU, Pith's permanent record of this paper and its review
CitationC.M. Arizmendi, M.E. Degaudenzi. "Wavelet Based Fractal Analysis of Airborne Pollen." arXiv:adap-org/9808004 (1998). https://pith.science/paper/DN6DQRXU
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 5,452 input tokens.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.15 · human participants 0.06 · controlled comparison 0.03 · randomized assignment 0.01 · states quantitative result 0.67 · compares with prior results 0.22 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

The most abundant biological particles in the atmosphere are pollen grains and spores. Self protection of pollen allergy is possible through the information of future pollen contents in the air. In spite of the importance of airborne pol len concentration forecasting, it has not been possible to predict the pollen concentrations with great accuracy, and about 25% of the daily pollen forecasts have resulted in failures. Previous analysis of the dynamic characteristics of atmospheric pollen time series indicate that the system can be described by a low dimensional chaotic map. We apply the wavelet transform to study the multifractal characteristics of an a irborne pollen time series. We find the persistence behaviour associated to low pollen concentration values and to the most rare events of highest pollen co ncentration values. The information and the correlation dimensions correspond to a chaotic system showing loss of information with time evolution.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 The most abundant biological particles in the atmosphere are pollen grains and spores. background 1.00 0.04 0.02 asserted 1.00
s1 Self protection of pollen allergy is possible through the information of future pollen contents in the air. background 1.00 0.04 0.04 hedged possibility 0.92
s2 In spite of the importance of airborne pol len concentration forecasting, it has not been possible to predict the pollen concentrations with great accuracy, and about 25% of the daily pollen forecasts have resulted in failures. gap 0.69 0.09 0.04 asserted 0.99
s3 Previous analysis of the dynamic characteristics of atmospheric pollen time series indicate that the system can be described by a low dimensional chaotic map. background 1.00 0.04 0.05 hedged possibility 0.82
s4 We apply the wavelet transform to study the multifractal characteristics of an a irborne pollen time series. method 0.81 0.95 0.05 asserted 0.95
s5 We find the persistence behaviour associated to low pollen concentration values and to the most rare events of highest pollen co ncentration values. result 1.00 0.96 0.43 asserted 1.00
s6 The information and the correlation dimensions correspond to a chaotic system showing loss of information with time evolution. interpretation 0.55 0.80 0.32 asserted 1.00

What kind of paper the classifier reports this is: empirical study 0.87 · evidence from analysis of existing data 0.93.

What was examined, and what was not

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not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
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  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

The most abundant biological particles in the atmosphere are pollen grains and spores. Self protection of pollen allergy is possible through the information of future pollen contents in the air. In spite of the importance of airborne pol len concentration forecasting, it has not been possible to predict the pollen concentrations with great accuracy, and about 25% of the daily pollen forecasts have resulted in failures. Previous analysis of the dynamic characteristics of atmospheric pollen time series indicate that the system can be described by a low dimensional chaotic map. We apply the wavelet transform to study the multifractal characteristics of an a irborne pollen time series. We find the persistence behaviour associated to low pollen concentration values and to the most rare events of highest pollen co ncentration values. The information and the correlation dimensions correspond to a chaotic system showing loss of information with time evolution.

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