{"id":"W4393716657","doi":"10.5281/zenodo.6532891","title":"SuperDARN data in netCDF format (2011-Oct)","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 graphics (images); 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":[0.000916109,0.001469907,0.0009690981,0.002989918,0.0006880904,0.002368999,0.002165598,0.001687886,0.1340186],"category_scores_gemma":[0.004833734,0.0005580968,0.001160344,0.004602535,0.0003280869,0.001943905,0.001867803,0.00174052,0.1982028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001501475,"about_ca_system_score_gemma":0.001849845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01834027,"about_ca_topic_score_gemma":0.0291858,"domain_scores_codex":[0.9992051,0.00009923144,0.0001094572,0.0002177599,0.0002313144,0.0001372424],"domain_scores_gemma":[0.9981955,0.0003284416,0.000150918,0.000493934,0.0006854038,0.0001458285],"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":[0.00003135486,0.00001030642,0.000444737,0.0002524979,0.00001222118,0.00001591286,0.00001406137,0.0001974924,0.00009730392,0.0003999672,0.996179,0.002345223],"study_design_scores_gemma":[0.00006174256,0.000006349405,0.002288179,0.0001531762,0.000009848417,0.00004015823,0.00006606409,0.0002511278,0.0003563926,0.001256017,0.9954921,0.00001874578],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009607997,0.0000307927,0.0001830437,0.00006095833,0.00003608876,0.00001065012,0.9976762,0.0007377084,0.00116845],"genre_scores_gemma":[0.0002999571,0.00003333045,0.0004764062,0.00004214147,0.000007698253,0.0000382853,0.9979535,0.000207421,0.0009411421],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1340186,"threshold_uncertainty_score":0.448337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0740659935261541,"score_gpt":0.3214640369164558,"score_spread":0.2473980433903017,"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."}}