{"id":"W2626100470","doi":"10.1016/j.icarus.2017.06.020","title":"Generating realistic synthetic meteoroid orbits","year":2017,"lang":"en","type":"article","venue":"Icarus","topic":"Astro and Planetary Science","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; National Aeronautics and Space Administration","keywords":"Meteoroid; Meteor shower; Meteor (satellite); Computer science; Orbit (dynamics); Synthetic data; Orbit determination; Algorithm; Astronomy; Physics; Aerospace engineering; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003503489,0.0005542751,0.0003230815,0.0004075401,0.0002575255,0.000488903,0.0007211503,0.001136191,0.002773883],"category_scores_gemma":[0.003048179,0.0004660622,0.0005068586,0.0004961814,0.0003806487,0.0003946781,0.0005705277,0.0005670146,0.0004655018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004683551,"about_ca_system_score_gemma":0.0006399558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005037363,"about_ca_topic_score_gemma":0.004019081,"domain_scores_codex":[0.9998202,0.00005824106,0.000008832064,0.00004202041,0.0000526747,0.00001804198],"domain_scores_gemma":[0.999323,0.0003779162,0.00005964987,0.00009492579,0.0001074137,0.00003701393],"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":[0.0001403257,0.00002862648,0.001422029,0.00004564101,0.00003694078,0.0001263643,0.00004450583,0.9859166,0.001339675,0.002228823,0.001451266,0.007219154],"study_design_scores_gemma":[0.00004790543,0.00002702177,0.0003079927,0.000005454106,0.000006291427,0.00003393791,0.00001734331,0.996675,0.000903242,0.001211215,0.0007593841,0.000005280743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6700634,0.0003094561,0.3017759,0.0007477895,0.0004388898,0.0002465631,0.00621287,0.003990218,0.01621479],"genre_scores_gemma":[0.9332182,0.00007901605,0.06033438,0.00007886985,0.00004136338,0.00009136105,0.004228243,0.0002181356,0.001710468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005037363,"threshold_uncertainty_score":0.01001608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01687213518279855,"score_gpt":0.2529860608954798,"score_spread":0.2361139257126812,"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."}}