{"id":"W4288284689","doi":"10.48550/arxiv.1907.05259","title":"Searching for Extraterrestrial Intelligence by Locating Potential ET Communication Networks in Space","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Space Science and Extraterrestrial Life","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Secretário de Ciência, Tecnologia e Ensino Superior, Governo do Estado de Parana; Universities Space Research Association; York University; National Aeronautics and Space Administration","keywords":"Search for extraterrestrial intelligence; Exoplanet; Extraterrestrial life; Solar System; Computer science; Telecommunications network; Planet; NASA Deep Space Network; Astrobiology; Spacecraft; Physics; Astronomy; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006877076,0.0002492991,0.0002992887,0.0001231448,0.0001473879,0.0002006141,0.0008575332,0.0001682925,0.00003797843],"category_scores_gemma":[0.00001801079,0.0002895365,0.0001693678,0.0002752859,0.0001044161,0.0003070088,0.0005592179,0.0007663306,0.00002549221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008607153,"about_ca_system_score_gemma":0.0002577917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003783519,"about_ca_topic_score_gemma":0.0001099818,"domain_scores_codex":[0.998369,0.0002462345,0.0002488745,0.0006496932,0.00007333769,0.0004128757],"domain_scores_gemma":[0.998741,0.0002113567,0.0002716633,0.0006143625,0.00006261604,0.0000990544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001207559,0.00006054351,0.006002275,0.00001477185,0.00002688308,0.000002137479,0.0001594824,0.947364,0.00009187472,0.04523062,0.0002912996,0.0006353614],"study_design_scores_gemma":[0.0006617189,0.00004473271,0.000193235,0.0002056625,0.00003818481,1.751361e-7,0.00130897,0.9636264,0.0001942748,0.03312191,0.0002139396,0.0003908167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4455256,0.00005043625,0.5513777,0.0001660322,0.0005309219,0.0006730695,0.00003571936,0.00002820679,0.001612257],"genre_scores_gemma":[0.9985108,0.00005672025,0.0003541843,0.00002457443,0.0002271959,0.000004803921,0.0002876924,0.00002152688,0.000512446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5529853,"threshold_uncertainty_score":0.9999557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.071746532400089,"score_gpt":0.2396955439809775,"score_spread":0.1679490115808885,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}