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MSc Thesis submission version
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.gitignore

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**/.env
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**/*.o
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**/*.mod
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**/*.a
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**/.DS_Store
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**/.ipynb_checkpoints
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/miniconda3

.gitmodules

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[submodule "sosaa"]
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path = sosaa
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url = https://github.com/juntyr/sosaa-10618aa.git
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[submodule "sosaa-data/trajectories"]
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path = sosaa-data/trajectories
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url = https://github.com/juntyr/sosaa-trajectories-dataset.git
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[submodule "sosaa-gui"]
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path = sosaa-gui
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url = https://github.com/juntyr/sosaa-gui.git

CITATION.cff

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# This CITATION.cff file was generated with cffinit.
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# Visit https://bit.ly/cffinit to generate yours today!
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cff-version: 1.2.0
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title: Prudent Response Surface Models
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message: >-
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If you use this work, please cite it using the metadata
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from this file.
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type: software
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authors:
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- given-names: Juniper
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family-names: Tyree
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affiliation: University of Helsinki
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orcid: 'https://orcid.org/0000-0002-7923-9609'
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- given-names: Michael
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family-names: Boy
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orcid: 'https://orcid.org/0000-0002-8107-4524'
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affiliation: 'University of Helsinki, LUT University'
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- given-names: Andreas
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family-names: Rupp
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affiliation: LUT University
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orcid: 'https://orcid.org/0000-0001-5527-7187'
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- given-names: Petri
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family-names: Clusius
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orcid: 'https://orcid.org/0000-0003-3121-0775'
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affiliation: University of Helsinki
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identifiers:
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- type: url
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value: >-
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https://github.com/juntyr/prudent-response-surface-models/releases/tag/msc-tcm
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description: The GitHub release
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repository-code: 'https://github.com/juntyr/prudent-response-surface-models'
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abstract: >-
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Prudent Response Surface Models combine predictions with
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confidence scores and uncertainty levels, allowing their
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use in downstream analysis even for high-uncertainty or
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out-of-distribution inputs.
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keywords:
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- SOSAA
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- response surface model
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- machine learning
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- out-of-distribution
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- uncertainty quantification
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license: CC-BY-4.0
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commit: msc-tcm
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version: 1.0.0
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date-released: '2023-04-27'

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