{"id":"W3097684409","doi":"10.1051/0004-6361/202038649","title":"FRIPON: a worldwide network to track incoming meteoroids","year":2020,"lang":"en","type":"article","venue":"Astronomy and Astrophysics","topic":"Astro and Planetary Science","field":"Physics and Astronomy","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science and Technology Facilities Council; Colegiul Consultativ pentru Cercetare-Dezvoltare şi Inovare; Centre National d’Etudes Spatiales; Observatoire de Paris, Université de Recherche Paris Sciences et Lettres; Sorbonne Université; Agence Nationale de la Recherche; Muséum National d'Histoire Naturelle; Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii; Centre National de la Recherche Scientifique; Ministério da Ciência, Tecnologia, Inovações e Comunicações; Istituto Nazionale di Astrofisica; Conseil Régional, Île-de-France","keywords":"Meteoroid; Meteorite; Interplanetary spaceflight; Event (particle physics); Interplanetary medium; Track (disk drive); Interplanetary dust cloud","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009740517,0.0008076775,0.0003973256,0.001942522,0.0003670036,0.0007334453,0.0009507268,0.0005656565,0.005815864],"category_scores_gemma":[0.001835278,0.0001795954,0.0002326657,0.001244715,0.0002029444,0.001371793,0.001410661,0.0005705522,0.002909463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006671885,"about_ca_system_score_gemma":0.00105996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01575572,"about_ca_topic_score_gemma":0.01507304,"domain_scores_codex":[0.9994181,0.00006934798,0.00002939587,0.0002251793,0.0001536375,0.000104262],"domain_scores_gemma":[0.9986926,0.0001248227,0.00030558,0.0002075228,0.0003758645,0.0002936944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0022576,0.0003507856,0.249244,0.001146626,0.0003773363,0.0009332175,0.001040501,0.01800123,0.04089873,0.004625455,0.2906924,0.3904322],"study_design_scores_gemma":[0.0003984878,0.0007631533,0.3041684,0.0003721892,0.0001956201,0.0007870545,0.001196326,0.08690953,0.01454946,0.002426915,0.5880763,0.00015652],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4767194,0.00587899,0.1291716,0.001883609,0.001058834,0.002447844,0.2658461,0.03213069,0.08486272],"genre_scores_gemma":[0.6133115,0.001226472,0.06313382,0.0003274897,0.0003728401,0.001019949,0.3019291,0.001040205,0.01763859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01575572,"threshold_uncertainty_score":0.03132802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0091661615021638,"score_gpt":0.1966886204740833,"score_spread":0.1875224589719195,"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."}}