{"id":"W4393480731","doi":"10.5281/zenodo.6533671","title":"SuperDARN data in netCDF format (2011-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; Data format; Geology; Computer science; Computer graphics (images); Database; 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":[0.0009506883,0.001492518,0.0009990337,0.003158215,0.0007134393,0.002393203,0.002226261,0.001673673,0.1320078],"category_scores_gemma":[0.004823375,0.0005686585,0.001179782,0.004841018,0.0003357386,0.001929748,0.001897942,0.001794853,0.1956931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001518102,"about_ca_system_score_gemma":0.001843157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01874029,"about_ca_topic_score_gemma":0.02978313,"domain_scores_codex":[0.9991892,0.0001019826,0.0001100694,0.0002230701,0.0002355447,0.0001402415],"domain_scores_gemma":[0.9981798,0.0003320941,0.0001546465,0.0005058149,0.0006824658,0.0001452611],"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":[0.00003120097,0.00001045078,0.0004522884,0.0002542714,0.00001262617,0.0000160908,0.00001434145,0.0002000738,0.00009851348,0.0004070583,0.9962201,0.002283028],"study_design_scores_gemma":[0.00006183283,0.00000597768,0.00227796,0.0001477601,0.000009831028,0.00003938871,0.0000641176,0.0002339445,0.0003367575,0.001233267,0.9955708,0.0000184103],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000966372,0.00003132217,0.0001771286,0.0000582562,0.00003663665,0.00001035802,0.9977424,0.0007026125,0.001144561],"genre_scores_gemma":[0.0002886292,0.00003304683,0.0004794263,0.00004013428,0.000007721651,0.00003826683,0.998007,0.0002072676,0.0008985223],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1320078,"threshold_uncertainty_score":0.4416102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07418918327014093,"score_gpt":0.3213882952093969,"score_spread":0.247199111939256,"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."}}