{"id":"W4398616074","doi":"10.7910/dvn/pkjufn/e5mtbe","title":"FCC2002.034.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Earth's magnetic field; Range (aeronautics); Meteorology; Ran; Environmental science; Atmospheric sciences; Remote sensing; Geography; Geology; Physics; Computer science; Engineering; Magnetic field; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008490389,0.003037887,0.00183271,0.003618098,0.001067266,0.003248251,0.003915398,0.002429612,0.1342547],"category_scores_gemma":[0.005033882,0.0008504057,0.001196498,0.006832036,0.00056717,0.001921843,0.002425752,0.001721406,0.2105569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00167503,"about_ca_system_score_gemma":0.002195133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03983309,"about_ca_topic_score_gemma":0.05114794,"domain_scores_codex":[0.9991065,0.0001333557,0.00007767168,0.0002910726,0.0001875523,0.0002038826],"domain_scores_gemma":[0.998219,0.0003096252,0.0001381337,0.0006111875,0.0004708547,0.0002511586],"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":[0.00003257074,0.00000843401,0.0002029749,0.0001662773,0.0000121382,0.000006941466,0.000007493378,0.0001491229,0.00004229173,0.0002504012,0.9983877,0.0007336764],"study_design_scores_gemma":[0.0002303381,0.00001613168,0.002005031,0.0001553119,0.00002039253,0.00002934856,0.00005020959,0.0006785247,0.0003578269,0.001435265,0.9949933,0.00002834713],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005386777,0.00003310566,0.00003349846,0.00004242039,0.00002172896,0.00000406296,0.9986442,0.0005544922,0.0006127169],"genre_scores_gemma":[0.0002910509,0.00003187675,0.0001134596,0.00003912059,0.000009906035,0.00002405215,0.9988079,0.0001268203,0.0005557949],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8657453,"threshold_uncertainty_score":0.4491266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008480041429497018,"score_gpt":0.2155780340902826,"score_spread":0.2070979926607855,"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."}}