{"id":"W4394021575","doi":"10.5281/zenodo.6520205","title":"SuperDARN data in netCDF format (2012-Jun)","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; Geology; Computer science; 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":[0.0009847962,0.001551139,0.001033167,0.003128207,0.0007312403,0.002481017,0.002262905,0.001662631,0.1426162],"category_scores_gemma":[0.005120196,0.0006006254,0.00123548,0.004821514,0.0003342442,0.001956013,0.001982525,0.001812263,0.2108106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001411258,"about_ca_system_score_gemma":0.001831019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01728058,"about_ca_topic_score_gemma":0.02822649,"domain_scores_codex":[0.9991492,0.0001068508,0.0001160015,0.0002351219,0.0002482909,0.0001444161],"domain_scores_gemma":[0.9981274,0.0003475387,0.0001555394,0.0005253392,0.0006915411,0.0001526707],"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":[0.00003062384,0.00001026235,0.0003969888,0.0002597077,0.00001249514,0.00001498161,0.00001380281,0.0001775873,0.00009652575,0.0003757638,0.9964407,0.002170558],"study_design_scores_gemma":[0.00006677367,0.000006289143,0.002102127,0.0001485643,0.0000103766,0.00003899646,0.00006064032,0.0002397534,0.0003353807,0.001306918,0.9956653,0.0000189113],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008956405,0.0000306078,0.0001857455,0.00005804503,0.00003856863,0.00001089964,0.9976341,0.0008025714,0.00114991],"genre_scores_gemma":[0.0002646909,0.00003261324,0.0005022824,0.00004070338,0.000008130995,0.00004164846,0.9979444,0.0002480409,0.0009174771],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1426162,"threshold_uncertainty_score":0.4770989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07485801907904206,"score_gpt":0.3233203215309489,"score_spread":0.2484623024519068,"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."}}