{"id":"W4393770383","doi":"10.5281/zenodo.6580443","title":"SuperDARN data in netCDF format (2008-Apr)","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; Computer science; Computer graphics (images); Database; Programming language; Computer hardware","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":[0.0009583895,0.001463304,0.0009650968,0.003141734,0.0006631726,0.002305528,0.002264053,0.001645503,0.1275595],"category_scores_gemma":[0.004883088,0.0005585113,0.001113776,0.004683583,0.0003255066,0.001893427,0.001830898,0.001774855,0.1893521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001479419,"about_ca_system_score_gemma":0.001796884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01772809,"about_ca_topic_score_gemma":0.02707752,"domain_scores_codex":[0.9991902,0.0001010669,0.0001087611,0.000225028,0.0002399386,0.0001350564],"domain_scores_gemma":[0.9980918,0.0003470841,0.0001641849,0.0005255204,0.000723833,0.0001475376],"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":[0.00002940758,0.00001028527,0.0004214713,0.0002312304,0.00001110125,0.0000145956,0.00001346418,0.0001785165,0.00009567153,0.0003853901,0.9964,0.00220901],"study_design_scores_gemma":[0.00006342257,0.000006031561,0.00221666,0.0001435416,0.000009000973,0.00003819131,0.00005979664,0.0002276936,0.0003302317,0.001141689,0.9957468,0.00001697952],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009935505,0.00002906009,0.0001773499,0.00005945777,0.00003564645,0.00001089963,0.9977095,0.0007218658,0.0011569],"genre_scores_gemma":[0.0002831277,0.00003071592,0.0005081905,0.00004098299,0.000007726273,0.00004058154,0.9979381,0.0002094449,0.0009411271],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1275595,"threshold_uncertainty_score":0.4267289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07200098395975892,"score_gpt":0.3224491284201009,"score_spread":0.250448144460342,"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."}}