{"id":"W2593231895","doi":"10.1111/maps.12856","title":"Meteor shower detection with density‐based clustering","year":2017,"lang":"en","type":"article","venue":"Meteoritics and Planetary Science","topic":"Astro and Planetary Science","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Aeronautics and Space Administration","keywords":"Meteor (satellite); Meteor shower; Cluster analysis; Sky; DBSCAN; Cluster (spacecraft); Computer science; Metric (unit); Algorithm; Remote sensing; Physics; Artificial intelligence; Meteorology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004405703,0.0001535516,0.0001497449,0.00008205955,0.001534933,0.0004905984,0.0004514513,0.00002134977,0.0001006741],"category_scores_gemma":[0.00001443662,0.0001211595,0.0000207801,0.0001005065,0.0007135241,0.0006292095,0.00007156769,0.0001439988,0.00001678757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006535127,"about_ca_system_score_gemma":0.00008003488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009083164,"about_ca_topic_score_gemma":0.0002323154,"domain_scores_codex":[0.9987756,0.00001789342,0.0001166524,0.0003936658,0.0003251817,0.0003709767],"domain_scores_gemma":[0.9991524,0.0000677055,0.00009262465,0.0004317948,0.00005519166,0.0002003451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008228293,0.00004056198,0.8761873,0.00002410527,0.00002849113,0.00004900481,0.0001498118,0.002222228,0.029102,0.0008483381,0.00002491858,0.09124092],"study_design_scores_gemma":[0.0005915081,0.0003519163,0.794467,0.00004150246,0.00005341558,0.00003164702,0.0001541874,0.1885479,0.01321619,0.0003306431,0.001721828,0.0004922624],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9474373,0.00002287772,0.04608911,0.00008360817,0.0003270381,0.0001203856,0.00005807252,0.00002052923,0.005841054],"genre_scores_gemma":[0.9913656,0.000001194964,0.008325129,0.00006541704,0.0001122845,0.00000197673,0.00002022286,0.000004620191,0.0001035945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1863257,"threshold_uncertainty_score":0.9997649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003380986701682,"score_gpt":0.2165440203628801,"score_spread":0.2065102104958633,"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."}}