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Evaluating Biosignatures for Life Detection

Authors: Pohorille, Andrew; Sokolowska, Joanna;

Evaluating Biosignatures for Life Detection

Abstract

Conceptual frameworks are developed for evaluating the ability of different biosignatures to provide evidence for the presence of life in planned missions or observational studies. The focus is on intrinsic characteristics of biosignatures in space environments rather than on their detection, which depends on technology. Evaluation procedures are drawn from extensive studies in decision theory on related problems in business, engineering, medical fields, and the social arena. Three approaches are particularly useful. Two of them, Signal Detection Theory and Bayesian hypothesis testing, are based on probabilities. The third approach is based on utility theory. In all the frameworks, knowledge about a subject matter has to be translated into probabilities and/or utilities in a multistep process called elicitation. We present the first attempt to cover all steps, from acquiring knowledge about biosignatures to assigning probabilities or utilities to global quantities, such as false positives and false negatives. Since elicitation involves human judgment that is always prone to perceptual and cognitive biases, the relevant biases are discussed and illustrated in examples. We further discuss at which stage of elicitation human judgment should be involved to ensure the most reliable outcomes. An example, how evaluating biosignatures might be implemented, is given in the Supplementary Information.

Keywords

Extraterrestrial Environment, Exobiology, Bayes Theorem, Research Articles, Probability

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    16
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    Top 10%
    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Average
Top 10%
Green
hybrid