Evidence map›Paper›PMID 28735343›Full record

ArticleJournal of mathematical biology2018

Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations.

David Koslicki, Mark Novak

Abstract read
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In one paragraph

Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

David KoslickiMathematics Department, Oregon State University, Corvallis, OR, USA. david.koslicki@math.oregonstate.edu.ORCID 0000-0002-0640-954X
Mark NovakDepartment of Untegrative Biology, Oregon State University, Corvallis, OR, USA.ORCID 0000-0002-7881-4253

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We consider the goal of predicting how complex networks respond to chronic (press) perturbations when characterizations of their network topology and interaction strengths are associated with uncertainty. Our primary result is the derivation of exact formulas for the expected number and probability of qualitatively incorrect predictions about a system's responses under uncertainties drawn form arbitrary distributions of error. Additional indices provide new tools for identifying which links in a network are most qualitatively and quantitatively sensitive to error, and for determining the volume of errors within which predictions will remain qualitatively determinate (i.e. sign insensitive). Together with recent advances in the empirical characterization of uncertainty in networks, these tools bridge a way towards probabilistic predictions of network dynamics.

Indexed as

Models, BiologicalAnimalsComputational BiologyEcosystemFood ChainHumansMathematical ConceptsProbabilitySystems BiologyUncertaintyCommunity matrixEcosystem-based managementIntraguild predationInverseLoop analysisMatrix perturbationNet effectsPress perturbationsQualitative indeterminacySherman–MorrisonSign patternSign sensitivityTrophic chain

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.