{"id":"W4307511657","doi":"10.1002/essoar.10512714.1","title":"Formation and motion of horse collar aurora events","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Science and Technology Facilities Council","keywords":"Collar; Motion (physics); Horse; Computer science; Geology; Engineering; Artificial intelligence; Mechanical 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":[],"consensus_categories":[],"category_scores_codex":[0.0001522804,0.0001198029,0.000154462,0.001032694,0.0005729781,0.0007370871,0.0001917481,0.0002303246,0.00172773],"category_scores_gemma":[0.0004595544,0.00008818175,0.0001343244,0.0004899342,0.000250286,0.0002479141,0.0005168062,0.0001859764,0.0003080613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003253719,"about_ca_system_score_gemma":0.000151771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008135983,"about_ca_topic_score_gemma":0.009633066,"domain_scores_codex":[0.999891,0.00001330636,0.000006518733,0.00003113914,0.00002407812,0.00003390233],"domain_scores_gemma":[0.9996769,0.0000261713,0.0001161109,0.00001979115,0.00005868132,0.0001023483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002708055,0.00004593008,0.9764352,0.00002676695,0.00003819241,0.001093568,0.001365558,0.0005291925,0.007950343,0.0003434571,0.0009246857,0.01097627],"study_design_scores_gemma":[0.000003216905,0.0000351576,0.997535,0.000004744502,0.000005944303,0.0001860345,0.0004188513,0.000323898,0.0003223954,0.00003456738,0.001126394,0.000003817029],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962225,0.0001247602,0.0001000262,0.00002192316,0.000007115278,0.00001471538,0.0002544078,0.000008315541,0.003246318],"genre_scores_gemma":[0.9989185,0.00005141731,0.0001183118,0.000007049854,0.000009838906,0.000004055988,0.0003837332,0.000002721592,0.0005043022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008135983,"threshold_uncertainty_score":0.01617724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007346305096033043,"score_gpt":0.2264518231995144,"score_spread":0.2191055181034814,"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."}}