{"id":"W4393453246","doi":"10.5281/zenodo.7613126","title":"SuperDARN data in netCDF format (2021-Nov)","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; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001060433,0.001442242,0.00103287,0.002985056,0.0008546155,0.003110732,0.002219522,0.001826571,0.3577322],"category_scores_gemma":[0.005141043,0.0007615816,0.001168077,0.004278021,0.0003342458,0.002957312,0.002238748,0.001978167,0.3665005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001323532,"about_ca_system_score_gemma":0.001804841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01651284,"about_ca_topic_score_gemma":0.02091871,"domain_scores_codex":[0.9991602,0.00008178005,0.00009734247,0.0001764966,0.000320784,0.0001634981],"domain_scores_gemma":[0.9976721,0.0003500006,0.000160469,0.0005803133,0.001062084,0.0001750835],"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":[0.0000432035,0.00001193488,0.0003802385,0.0001690542,0.000008164725,0.00001846531,0.00001504859,0.0002127488,0.0001612061,0.0004816166,0.9950259,0.003472342],"study_design_scores_gemma":[0.00007351636,0.000007269498,0.00180132,0.0001149942,0.000006751084,0.00003493284,0.00006295473,0.0002961865,0.0005635585,0.001552548,0.9954633,0.00002275679],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001904328,0.0000311921,0.0006173986,0.0001310319,0.0001295773,0.00003147409,0.9906545,0.002728213,0.005486112],"genre_scores_gemma":[0.0007473807,0.00004605256,0.001605687,0.0001090874,0.00002977818,0.00008428982,0.9918349,0.001596713,0.003946194],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3577322,"threshold_uncertainty_score":0.9161171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08526974383250391,"score_gpt":0.3364864518556336,"score_spread":0.2512167080231297,"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."}}