{"id":"W1642983250","doi":"","title":"THE MILLMAN FIREBALL ARCHIVE","year":2003,"lang":"en","type":"article","venue":"Journal of the Royal Astronomical Society of Canada","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Meteoroid; Population; Event (particle physics); Physics; Astrophysics; Astronomy; Demography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004684099,0.00007784927,0.0001728466,0.000004558668,0.0002894272,0.00004973837,0.0009616808,0.0000187951,0.00001459873],"category_scores_gemma":[0.00005281524,0.00004029736,0.0004295009,0.00007875992,0.00009117323,0.00005390861,0.0001239276,0.0002220142,2.264904e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001340491,"about_ca_system_score_gemma":0.000651632,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01038955,"about_ca_topic_score_gemma":0.01686651,"domain_scores_codex":[0.9989471,0.00007530973,0.0003716974,0.00007769431,0.0003070269,0.0002212127],"domain_scores_gemma":[0.9989891,0.0001715805,0.0004473184,0.0002221804,0.00007059723,0.00009922695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004289685,0.0001012272,0.01726669,0.00002077974,0.001227194,0.000002098405,0.0009434513,0.3413774,0.0002257099,0.02479765,0.5801759,0.03381898],"study_design_scores_gemma":[0.0007949048,0.0002064534,0.05649822,0.00006647714,0.00008837033,0.00001388981,0.001029014,0.3828077,0.001630518,0.002648836,0.5539165,0.0002990842],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.902732,0.001001948,0.07144374,0.01965485,0.001643431,0.0001420694,0.00001056218,0.000007471501,0.003363986],"genre_scores_gemma":[0.9811862,0.000002410909,0.01795789,0.0001240644,0.00008862214,2.857441e-7,6.857135e-8,0.000004002948,0.0006365132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0784542,"threshold_uncertainty_score":0.9962003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003894002339473539,"score_gpt":0.158642818461563,"score_spread":0.1547488161220895,"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."}}