{"id":"W4393710459","doi":"10.5281/zenodo.7823639","title":"SuperDARN Grid data in netCDF format (2020-May)","year":2023,"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; Grid; Computer science; Grid cell; Database; Computer graphics (images); Geology; Programming language; Geodesy","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":[0.0008900736,0.001097854,0.0008285709,0.002724248,0.0006939417,0.002752016,0.001844872,0.001456228,0.2625133],"category_scores_gemma":[0.004497201,0.0006329505,0.0009918464,0.004936966,0.0002697043,0.00245588,0.001867773,0.001616177,0.2630007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001362211,"about_ca_system_score_gemma":0.001718635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02425218,"about_ca_topic_score_gemma":0.02849225,"domain_scores_codex":[0.9993364,0.0000640963,0.00007180082,0.0001405965,0.0002515222,0.000135544],"domain_scores_gemma":[0.9979906,0.0002470644,0.0001512027,0.0004834712,0.0009497727,0.0001778679],"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":[0.00004006931,0.00000948976,0.0004355437,0.0001256941,0.00000780908,0.00001369268,0.00001538922,0.0002346138,0.0001119967,0.0005632839,0.9954281,0.003014412],"study_design_scores_gemma":[0.00006679253,0.000005652561,0.002123182,0.00008762097,0.00000590455,0.00002268982,0.00007128671,0.0003064845,0.0003852188,0.001381719,0.9955249,0.00001827895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002062507,0.00002810309,0.0004322967,0.0001404683,0.0001246106,0.00002247049,0.9914476,0.002143921,0.005454282],"genre_scores_gemma":[0.0009930091,0.00004799687,0.00146858,0.0001055548,0.00002659681,0.00006958261,0.99217,0.00126943,0.003849257],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2625133,"threshold_uncertainty_score":0.8781944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07745138925730626,"score_gpt":0.3353305417016449,"score_spread":0.2578791524443386,"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."}}