Evidence map›Paper›PMID 30275310›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2018

Bayesian approach to SETI.

Claudio Grimaldi, Geoffrey W Marcy

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Claudio GrimaldiLaboratory of Physics of Complex Matter, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; claudio.grimaldi@epfl.ch geoff.w.marcy@gmail.com.
Geoffrey W MarcyDepartment of Astronomy, University of California, Berkeley, CA 94720 claudio.grimaldi@epfl.ch geoff.w.marcy@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The search for technosignatures from hypothetical galactic civilizations is going through a new phase of intense activity. For the first time, a significant fraction of the vast search space is expected to be sampled in the foreseeable future, potentially bringing informative data about the abundance of detectable extraterrestrial civilizations or the lack thereof. Starting from the current state of ignorance about the galactic population of nonnatural electromagnetic signals, we formulate a Bayesian statistical model to infer the mean number of radio signals crossing Earth, assuming either nondetection or the detection of signals in future surveys of the Galaxy. Under fairly noninformative priors, we find that not detecting signals within about 1 kly from Earth, while suggesting the lack of galactic emitters or at best the scarcity thereof, is nonetheless still consistent with a probability exceeding 10% that typically over [Formula: see text] signals could be crossing Earth, with radiated power analogous to that of the Arecibo radar, but coming from farther in the Milky Way. The existence in the Galaxy of potentially detectable Arecibo-like emitters can be reasonably ruled out only if all-sky surveys detect no such signals up to a radius of about 40 kly, an endeavor requiring detector sensitivities thousands times higher than those of current telescopes. Conversely, finding even one Arecibo-like signal within [Formula: see text] light years, a possibility within reach of current detectors, implies almost certainly that typically more than [Formula: see text] signals of comparable radiated power cross the Earth, yet to be discovered.

Indexed as

Bayesian analysisMilky Wayprobabilityradio telescopeSETI

Identifiers

PMID30275310
PMCPMC6196512

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.