Evidence map›Paper›PMID 36745613›Full record

ArticlePloS one2023

`Friend or foe' and decision making initiative in complex conflict environments.

Mathew Zuparic, Sergiy Shelyag, Maia Angelova, Ye Zhu, Alexander Kalloniatis

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Mathew ZuparicDefence Science and Technology Group, Canberra, ACT, Australia.ORCID 0000-0003-0553-5023
Sergiy ShelyagSchool of IT, Deakin University, Melbourne, VIC, Australia.ORCID 0000-0002-6436-9347
Maia AngelovaSchool of IT, Deakin University, Melbourne, VIC, Australia.ORCID 0000-0002-0931-0916
Ye ZhuSchool of IT, Deakin University, Melbourne, VIC, Australia.
Alexander KalloniatisDefence Science and Technology Group, Canberra, ACT, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a novel mathematical model of two adversarial forces in the vicinity of a non-combatant population in order to explore the impact of each force pursuing specific decision-making strategies. Each force has the opportunity to draw support by enabling the decision-making initiative of the population, in tension with maintaining tactical and organisational effectiveness over their adversary. Each dynamic model component of force, population and decision-making, is defined by the archetypal Lanchester, Lotka-Volterra and Kuramoto-Sakaguchi models, with feedback between each component adding heterogeneity. Developing a scheme where cultural factors determine decision-making strategies for each force, this work highlights the parametric and topological factors that influence favourable results in a non-linear system where physical outcomes are highly dependent on the non-physical and cognitive nature of each force's intended strategy.

Indexed as

Decision MakingModels, Theoretical

Identifiers

PMID36745613
PMCPMC9901805

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.