Samantha Low‐Choy

ORCID: 0000-0002-1722-4428
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About
Contact & Profiles
Research Areas
  • Species Distribution and Climate Change
  • Ecology and Vegetation Dynamics Studies
  • Wildlife Ecology and Conservation
  • Bayesian Modeling and Causal Inference
  • Statistical Methods and Bayesian Inference
  • Bayesian Methods and Mixture Models
  • Air Quality and Health Impacts
  • Genetic and phenotypic traits in livestock
  • Economic and Environmental Valuation
  • Big Data and Business Intelligence
  • Data Analysis with R
  • Land Use and Ecosystem Services
  • Biomedical Text Mining and Ontologies
  • Semantic Web and Ontologies
  • Forecasting Techniques and Applications
  • Coral and Marine Ecosystems Studies
  • Statistical Methods and Inference
  • Soil Geostatistics and Mapping
  • Cardiac Health and Mental Health
  • Wildlife-Road Interactions and Conservation
  • Air Quality Monitoring and Forecasting
  • Telemedicine and Telehealth Implementation
  • Animal Disease Management and Epidemiology
  • Patient Satisfaction in Healthcare
  • Educational Environments and Student Outcomes

Griffith University
2015-2025

Office of Education
2024

University of Toronto
2022-2024

UNSW Sydney
2020

Queensland University of Technology
2009-2019

Plant Biosecurity Cooperative Research Centre
2011-2017

ACT Government
2011-2017

University of Canberra
2017

Australian Mathematical Sciences Institute
2009-2012

New York State Psychiatric Institute
2008-2009

A common feature of ecological data sets is their tendency to contain many zero values. Statistical inference based on such are likely be inefficient or wrong unless careful thought given how these zeros arose and best model them. In this paper, we propose a framework for understanding zero-inflated originate deciding We define classify the different kinds that occur in describe they arise: either from 'true zero' 'false observations. After reviewing recent developments modelling sets, use...

10.1111/j.1461-0248.2005.00826.x article EN Ecology Letters 2005-10-06

Bayesian statistical modeling has several benefits within an ecological context. In particular, when observed data are limited in sample size or representativeness, then the framework provides a mechanism to combine with other “prior” information. Prior information may be obtained from earlier studies, their absence, expert knowledge. This use of reflects scientific “learning cycle,” where prior initial estimates updated new become available. this paper we outline for design elicitation...

10.1890/07-1886.1 article EN Ecology 2009-01-01

Summary 1. Species’ distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical might be better management. A less expensive source of species’ information is expert opinion. This study evaluates knowledge and its source. In particular, we determine whether built apply over multiple regions or only within region where was derived. 2. The case focuses brush‐tailed rock‐wallaby Petrogale...

10.1111/j.1365-2664.2009.01671.x article EN Journal of Applied Ecology 2009-06-05

We consider the problem of combining opinions from different experts in an explicitly model-based way to construct a valid subjective prior Bayesian statistical approach. propose generic approach by considering hierarchical model accounting for various sources variation as well potential dependence between experts. apply this two problems. The first deals with food risk assessment involving modelling dose-response Listeria monocytogenes contamination mice. Two levels are considered (between...

10.1214/12-ba717 article EN Bayesian Analysis 2012-09-01

Photoluminescent metal–organic frameworks (MOFs) were grown in a living plant (Syngonium podophyllum) via immersing their roots an aqueous solution of disodium terephthalate and terbium chloride hexahydrate sequentially for 12 h without affecting viability. Then, app-assisted MOF–plant nanobiohybrids used the detection various toxic metal ions organic pollutants. Their performance sensing mechanism also evaluated. The results demonstrated that plants served as self-powered preconcentrators...

10.1021/acs.est.0c04688 article EN Environmental Science & Technology 2020-08-14

Teachers have professional obligations to incorporate Indigenous perspectives in their teaching but face challenges due Western-centric priorities schools, denying students the benefits gained from knowledge. A study conducted with 16 educators Australia, New Zealand, Canada, and United States offers unique insights into negotiating this problem. The Weaving Stories of Strength project synthesises Western qualitative research methods reveal practical solutions enhance teachers' confidence...

10.1016/j.tate.2024.104513 article EN cc-by Teaching and Teacher Education 2024-02-28

Expert knowledge is a valuable source of information with wide range research applications. Despite the recent advances in defining expert knowledge, little attention has been given to how view expertise as system interacting contributory factors for quantifying an individual's expertise. We present systems approach that accounts many contributing and their inter-relationships allows quantification A Bayesian network (BN) was chosen this purpose. For illustration, we focused on taxonomic The...

10.1002/ece3.926 article EN cc-by Ecology and Evolution 2013-12-26

Abstract Numerous expert elicitation methods have been suggested for generalised linear models (GLMs). This paper compares three relatively new approaches to eliciting knowledge in a form suitable Bayesian logistic regression. These were trialled on two experts order model the habitat suitability of threatened Australian brush‐tailed rock‐wallaby ( Petrogale penicillata ). The first approach is geographically assisted indirect predictive method with geographic information system (GIS)...

10.1002/env.935 article EN Environmetrics 2008-07-09

Abstract Bayesian networks (BNs) are becoming increasingly common in problems with spatial aspects. The degree of involvement may range from mapping BN outputs based on nodes the that explicitly involve geographic features, to integration different information. In these situations, it is useful consider how information systems (GISs) could be used enhance conceptualization, quantification, and prediction BNs. Here, we discuss some techniques integrate GIS models, reference recent literature...

10.1002/ieam.262 article EN Integrated Environmental Assessment and Management 2011-08-18

Abstract When modelling the distribution of a species, it is often not possible to comprehensively sample whole species and managers may have habitat models based on data from one area that they want apply in other areas. Hence, an important question is: how accurate are distributions when applied beyond areas where were developed? A first step measuring model transferability could be testing adjacent We predicted associations brush‐tailed rock‐wallaby ( Petrogale penicillata ) across two...

10.1111/j.1442-9993.2010.02122.x article EN Austral Ecology 2010-04-19
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