{"id":"W4393568086","doi":"10.5281/zenodo.7652992","title":"SuperDARN Grid data in netCDF format (1995-May)","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; Computer graphics (images); Grid cell; 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":[0.0007834201,0.0009358891,0.0007303944,0.003201763,0.0007158922,0.002432965,0.001804769,0.0009939015,0.2028861],"category_scores_gemma":[0.003996224,0.0005706782,0.0007215305,0.006412583,0.0002085231,0.001792149,0.001230117,0.001363954,0.1628536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001877603,"about_ca_system_score_gemma":0.002144222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05488396,"about_ca_topic_score_gemma":0.05050675,"domain_scores_codex":[0.9993414,0.0000522706,0.00007351609,0.0001213778,0.0002930272,0.000118314],"domain_scores_gemma":[0.9979746,0.000190658,0.0001613859,0.0004490883,0.001070678,0.0001535497],"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":[0.00005347381,0.00001050402,0.0006239916,0.00008910811,0.000008808723,0.0000197059,0.00001633237,0.0002940712,0.0001217356,0.0007857346,0.994255,0.003721376],"study_design_scores_gemma":[0.00005950126,0.000004807628,0.003737127,0.00006523434,0.000006271237,0.00002455958,0.00006594121,0.0002486671,0.0004017743,0.001023524,0.9943467,0.00001593768],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003456348,0.00003186879,0.0004107636,0.0001245738,0.000116224,0.00002420709,0.9902682,0.001213733,0.007464755],"genre_scores_gemma":[0.001204801,0.00004499198,0.001249978,0.00005926765,0.00002132972,0.00005288388,0.9919939,0.0006582343,0.004714608],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2028861,"threshold_uncertainty_score":0.6787215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07445418463398518,"score_gpt":0.2835734395306752,"score_spread":0.20911925489669,"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."}}