{"id":"W4394021477","doi":"10.5281/zenodo.7651303","title":"SuperDARN Grid data in netCDF format (2009-Aug)","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"NetCDF; Grid; Computer science; Database; Geology; Geodesy; 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":[0.0008330981,0.001072064,0.0008953115,0.00280769,0.0008200461,0.002574421,0.00200689,0.001371046,0.2450695],"category_scores_gemma":[0.004010587,0.000662838,0.0009524136,0.005061007,0.0002629514,0.002297924,0.001667448,0.001818849,0.2313517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001441191,"about_ca_system_score_gemma":0.001795651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02880417,"about_ca_topic_score_gemma":0.0337978,"domain_scores_codex":[0.999302,0.00005911014,0.00007433578,0.0001420836,0.0002894757,0.0001329203],"domain_scores_gemma":[0.9980843,0.0002052634,0.0001394641,0.0004957803,0.0009258386,0.0001493946],"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":[0.00004508297,0.00001136454,0.0004812466,0.0001080139,0.000008927454,0.00001796709,0.00001458065,0.0002651121,0.0001458773,0.0005737971,0.9953909,0.002936994],"study_design_scores_gemma":[0.00008298711,0.000005829378,0.002880522,0.00008017976,0.00000724505,0.00002855325,0.00006374839,0.0003591143,0.00053731,0.001409976,0.9945235,0.00002101265],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002879282,0.00002809588,0.0005278863,0.000137667,0.0001413557,0.00002489798,0.9900546,0.002161721,0.006635878],"genre_scores_gemma":[0.001040494,0.000041686,0.00157468,0.00008129314,0.00002418835,0.0000592334,0.9920203,0.00119473,0.003963253],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2450695,"threshold_uncertainty_score":0.819839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06439536186908518,"score_gpt":0.2749664914994708,"score_spread":0.2105711296303857,"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."}}