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Ours could realistically be the generation to discover evidence of life beyond Earth. With this privileged potential comes responsibility. The magnitude of the question, are we alone?, and the public interest therein, opens the possibility that results may be taken to imply more than the observations support, or than the observers intend. As life detection objectives become increasingly prominent in space sciences, it is essential to open a community dialog about how to convey information in a subject matter that is diverse, complicated, and has high potential to be sensationalized. Establishing best practices for communicating about life detection can serve to set reasonable expectations on the early stages of a hugely challenging endeavor, attach value to incremental steps along the path, and build public trust by making clear that false starts and dead ends are an expected and potentially productive part of the scientific process. Here, we endeavor to motivate and seed the discussion with basic considerations and offer an example of how such considerations might be incorporated and applied in a proof-of-concept-level framework. Everything mentioned herein, including the name of the confidence scale, is intended not as a prescription, but simply as the beginning of an important dialogue.
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Several exoplanets have been discovered to date, and the next step is the search for extraterrestrial life. However, it is difficult to estimate the number of life-bearing exoplanets because our only template is based on life on Earth. In this paper, a new approach is introduced to estimate the probability that life on Earth has survived from birth to the present based on its terrestrial extinction history. A histogram of the extinction intensity during the Phanerozoic Eon is modeled effectively with a log-normal function, supporting the idea that terrestrial extinction is a random multiplicative process. Assuming that the fitted function is a probability density function of extinction intensity per unit time, the estimated survival probability of life on Earth is ~0.15 from the beginning of life to the present. This value can be a constraint on $f_i$ in the Drake equation, which contributes to estimating the number of life-bearing exoplanets.
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Publication statistics are ubiquitous in the ratings of scientific achievement, with citation counts and paper tallies factoring into an individuals consideration for postdoctoral positions, junior faculty, tenure, and even visa status for international scientists. Citation statistics are designed to quantify individual career achievement, both at the level of a single publication, and over an individuals entire career. While some academic careers are defined by a few significant papers (possibly out of many), other academic careers are defined by the cumulative contribution made by the authors publications to the body of science. Several metrics have been formulated to quantify an individuals publication career, yet none of these metrics account for the dependence of citation counts and journal size on time. In this paper, we normalize publication metrics across both time and discipline in order to achieve a universal framework for analyzing and comparing scientific achievement. We study the publication careers of individual authors over the 50-year period 1958-2008 within six high-impact journals: CELL, the New England Journal of Medicine (NEJM), Nature, the Proceedings of the National Academy of Science (PNAS), Physical Review Letters (PRL), and Science. In comparing the achievement of authors within each journal, we uncover quantifiable statistical regularity in the probability density function (pdf) of scientific achievement across both time and discipline. The universal distribution of career success within these arenas for publication raises the possibility that a fundamental driving force underlying scientific achievement is the competitive nature of scientific advancement.
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