{"id":"W4393687430","doi":"10.5281/zenodo.6808393","title":"SuperDARN data in netCDF format (1998-Aug)","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":[0.0009000517,0.001468037,0.0009777709,0.003389975,0.000679644,0.002267807,0.002239499,0.001529671,0.1299324],"category_scores_gemma":[0.004566966,0.0005651994,0.001054748,0.005572009,0.0003001601,0.001801311,0.001676067,0.00172813,0.1902269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456483,"about_ca_system_score_gemma":0.001720103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02034653,"about_ca_topic_score_gemma":0.02770867,"domain_scores_codex":[0.9992324,0.00008687095,0.0001025666,0.0002137805,0.0002354072,0.0001290215],"domain_scores_gemma":[0.9981226,0.0003201787,0.0001662954,0.0005192707,0.0007253415,0.0001462285],"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":[0.00003355583,0.00001060882,0.000443387,0.000210551,0.00001092432,0.00001568093,0.00001362326,0.0001852718,0.00009757208,0.0003982921,0.9962263,0.002354223],"study_design_scores_gemma":[0.00006271576,0.000005463527,0.002260179,0.0001223487,0.000008417598,0.00003474951,0.00005732166,0.0002011939,0.0003052772,0.001038006,0.995889,0.00001529586],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000995059,0.00002583798,0.0001592611,0.00005008001,0.00003247101,0.000009605033,0.9978369,0.0006169532,0.001169295],"genre_scores_gemma":[0.0002748079,0.00002772844,0.0004359313,0.0000308079,0.000007082702,0.00003493583,0.998121,0.0001924971,0.0008752675],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1299324,"threshold_uncertainty_score":0.4346672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07646786845529513,"score_gpt":0.3262939973636579,"score_spread":0.2498261289083628,"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."}}