{"id":"W4393597286","doi":"10.5281/zenodo.6476643","title":"SuperDARN data in netCDF format (2014-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; 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":[0.000998441,0.001497427,0.000995994,0.003052527,0.000718283,0.002449706,0.002306229,0.001643423,0.141967],"category_scores_gemma":[0.005269459,0.0005860192,0.001218041,0.004552181,0.0003510668,0.00197452,0.00201767,0.001776351,0.2060754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001427573,"about_ca_system_score_gemma":0.001863886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01687034,"about_ca_topic_score_gemma":0.02698725,"domain_scores_codex":[0.9991465,0.0001091077,0.0001172632,0.000233648,0.0002479653,0.0001455218],"domain_scores_gemma":[0.9980952,0.0003554452,0.0001557342,0.0005278795,0.0007125269,0.0001531806],"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":[0.00003058961,0.0000101603,0.0004183912,0.0002561408,0.00001285531,0.00001470058,0.00001404326,0.0001827703,0.00009447808,0.0003973449,0.996428,0.002140708],"study_design_scores_gemma":[0.0000680044,0.000006367453,0.002053235,0.0001539126,0.00001022479,0.00003774641,0.00006257617,0.0002309282,0.000330011,0.001382085,0.9956462,0.00001865675],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000940436,0.00003223055,0.0001874276,0.00006230699,0.00004318398,0.00001164093,0.9976133,0.0007764864,0.001179338],"genre_scores_gemma":[0.0002908495,0.00003520215,0.0005096616,0.00004490086,0.000008910756,0.00004431685,0.9978581,0.0002489738,0.0009589829],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.141967,"threshold_uncertainty_score":0.4749271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06764638614007122,"score_gpt":0.3218086954409051,"score_spread":0.2541623093008338,"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."}}