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description
| - wetenschappelijk artikel (nl)
- article scientifique publié en 2019 (fr)
- artículu científicu espublizáu en marzu de 2019 (ast)
- scientific article published on 29 March 2019 (en)
- наукова стаття, опублікована 29 березня 2019 (uk)
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publication date
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publication date
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author name string
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author name string
| - David Morley
- Frances Garden
- Edward Jegasothy
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rdfs:label
| - Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO2 for a birth cohort in Sydney, Australia (en)
- Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO2 for a birth cohort in Sydney, Australia (nl)
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skos:prefLabel
| - Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO2 for a birth cohort in Sydney, Australia (en)
- Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO2 for a birth cohort in Sydney, Australia (nl)
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name
| - Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO2 for a birth cohort in Sydney, Australia (en)
- Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO2 for a birth cohort in Sydney, Australia (nl)
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author
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author
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title
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title
| - Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO2 for a birth cohort in Sydney, Australia (en)
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main subject
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PubMed ID
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published in
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published in
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volume
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number of pages
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number of pages
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DOI
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DOI
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DOI
| - 10.1016/J.ENVRES.2019.03.068
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