{"id":"W4393822035","doi":"10.5281/zenodo.6423467","title":"SuperDARN data in netCDF format (2016-May)","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"NetCDF; Computer science; Computer graphics (images); Database; Geology; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009848492,0.001457212,0.0009874029,0.002984981,0.0006893579,0.002478031,0.002256014,0.001641996,0.1364599],"category_scores_gemma":[0.005253038,0.0005466862,0.001193283,0.00444527,0.000344333,0.002006001,0.002013679,0.001738588,0.203888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001460629,"about_ca_system_score_gemma":0.001830746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01730852,"about_ca_topic_score_gemma":0.02789345,"domain_scores_codex":[0.9991835,0.0001058258,0.0001137772,0.0002267799,0.000233448,0.0001367038],"domain_scores_gemma":[0.9981425,0.0003354869,0.000155617,0.0005080522,0.000703159,0.0001551563],"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":[0.00003307456,0.00001022765,0.0004724682,0.000263545,0.00001275272,0.00001598845,0.00001530171,0.0001833424,0.0000964727,0.0004184661,0.9961259,0.002352444],"study_design_scores_gemma":[0.00006298377,0.000006074945,0.002052236,0.0001614466,0.000009456575,0.00003879655,0.00006639438,0.0002213346,0.0003239189,0.001352845,0.9956871,0.00001746098],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009897094,0.0000367697,0.000191853,0.00006778783,0.00004440642,0.00001170126,0.997552,0.0007833055,0.001213228],"genre_scores_gemma":[0.0003225462,0.00003894111,0.0005207752,0.00004876848,0.000009487929,0.00004292895,0.9977715,0.0002364899,0.001008598],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1364599,"threshold_uncertainty_score":0.4565037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07434652599597244,"score_gpt":0.3262595784004901,"score_spread":0.2519130524045177,"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."}}