{"id":"W4393481239","doi":"10.5281/zenodo.6726577","title":"SuperDARN data in netCDF format (2004-Sep)","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; Computer science; Geology; 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":[0.0009332124,0.001436485,0.0009953049,0.003272083,0.0006692851,0.002322632,0.002318653,0.001630273,0.1235285],"category_scores_gemma":[0.004928943,0.0005809568,0.001159574,0.005402729,0.0003118401,0.001790939,0.001628678,0.001752152,0.1794942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001658134,"about_ca_system_score_gemma":0.00198772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02224588,"about_ca_topic_score_gemma":0.02942037,"domain_scores_codex":[0.9991842,0.0001004149,0.0001133116,0.0002189949,0.0002438523,0.0001392327],"domain_scores_gemma":[0.9980236,0.0003392702,0.0001713719,0.000540327,0.0007708351,0.0001546421],"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":[0.00003198144,0.00001091474,0.0004287219,0.000213211,0.00001214864,0.00001544001,0.00001287538,0.0002095806,0.00009282272,0.0004020169,0.9963517,0.002218546],"study_design_scores_gemma":[0.00006650924,0.000006161947,0.002470731,0.0001352804,0.000009750718,0.0000379448,0.00005798612,0.0002552723,0.000348547,0.001187233,0.9954066,0.00001785527],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000955504,0.00002689754,0.0001675354,0.0000550508,0.00003256443,0.000009858203,0.9978688,0.0006587242,0.001085097],"genre_scores_gemma":[0.0002733611,0.00002811806,0.0004315345,0.00003381705,0.000006695894,0.00003382298,0.9981409,0.000183703,0.0008678963],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1235285,"threshold_uncertainty_score":0.4132438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07170136764033479,"score_gpt":0.324272260279893,"score_spread":0.2525708926395582,"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."}}