{"id":"W4393744551","doi":"10.5281/zenodo.8274624","title":"SuperDARN Grid data in netCDF format (2016-Apr)","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; Grid cell; Geology; Computer graphics (images); Operating system; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.002071673,0.0003241813,0.0003782687,0.0005820202,0.001234066,0.002663026,0.01220943,0.0002080754,0.0006264051],"category_scores_gemma":[0.0007312014,0.0003386567,0.00006347863,0.001545893,0.00009601415,0.0007810342,0.01375446,0.0007595902,0.07202716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001828458,"about_ca_system_score_gemma":0.00002472543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003611549,"about_ca_topic_score_gemma":0.000005989024,"domain_scores_codex":[0.9961561,0.0006143354,0.0006042204,0.001105813,0.0007619044,0.0007576511],"domain_scores_gemma":[0.9957092,0.00007757471,0.0002333806,0.003431473,0.0003174547,0.0002309216],"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":[0.00000830536,0.00007755035,3.311526e-7,0.0001709634,0.00002916362,0.0000909439,0.0001362867,0.0001094778,0.000003677224,0.0002427444,0.9909344,0.008196104],"study_design_scores_gemma":[0.0003706979,0.000103282,0.00005512694,0.0001821405,0.000008629125,0.0001381979,0.00003669079,0.005492148,0.00000100499,0.00006761906,0.9931871,0.0003573205],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001653471,0.0001440679,0.01008612,0.000489739,0.001206483,0.0005078612,0.9827998,0.00136863,0.003380754],"genre_scores_gemma":[0.0002284883,0.0002707653,0.0001861765,0.0001225711,0.0004759059,5.682172e-8,0.9975478,0.0006787101,0.0004895104],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07140075,"threshold_uncertainty_score":0.9999065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06550178611028622,"score_gpt":0.2740641718525966,"score_spread":0.2085623857423103,"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."}}