Subjects » Calibration/tuning
Parent Confirmation & evaluation
References (10)
The subject ‘Calibration/tuning’ is applied to these references.
Machine learning and the quest for objectivity in climate model parameterization. Climatic Change. 2023
Calibration/tuning, Expert judgement, Machine Learning, Values
Can Machines Learn How Clouds Work? The Epistemic Implications of Machine Learning Methods in Climate Science. Philosophy of Science. 2021
Model-Selection Theory: The Need for a More Nuanced Picture of Use-Novelty and Double-Counting. The British Journal for the Philosophy of Science. 2018
Calibration/tuning, Confirmation & evaluation
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A discussion regarding double-counting in climate modeling, arguing that the use-novel intuition largely held in the scientific community, that data used in tuning cannot be used in confirmation, is too crude. Steele and Werndl maintain that the prominent logics of confirmation do not, for varying reasons, support this intuitive position in full.
Practice and philosophy of climate model tuning across six US modeling centers. Geoscientific Model Development. 2017
Calibration/tuning, Confirmation & evaluation, Ensemble methods
The Art and Science of Climate Model Tuning. Bulletin of the American Meteorological Society. 2017
Calibration/tuning, Confirmation & evaluation, Parameterization
Predictivism and old evidence: a critical look at climate model tuning. European Journal for Philosophy of Science. 2015
Calibration/tuning, Confirmation & evaluation, Confirmational holism
Predictivism and old evidence: a critical look at climate model tuning. European Journal for Philosophy of Science. 2015
A practical philosophy of complex climate modelling. European Journal for Philosophy of Science. 2014
Climate Models, Calibration, and Confirmation. The British Journal for the Philosophy of Science. 2013
Calibration/tuning, Confirmation & evaluation
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A discussion of the problem of double-counting in climate modeling, specifically when the same evidence is used to both calibrate a model and then confirm the adequacy of the results. Steele and Werndl turn to a Baysian approach to argue for a method of incremental confirmation, making double-counting unproblematic. For a response to this argument see Mathias Frisch’s 2015 paper “Predictivism and old evidence: a critical look at climate model tuning”.
Confidence, uncertainty and decision-support relevance in climate predictions. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2007
Calibration/tuning, Decision-making, Reliability & uncertainty