{"id":"W4393752358","doi":"10.5281/zenodo.7823886","title":"SuperDARN Grid data in netCDF format (2019-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; Computer graphics (images); 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":[0.0007819329,0.001048287,0.0008103263,0.002518362,0.0007067075,0.002609557,0.001772529,0.00138551,0.25982],"category_scores_gemma":[0.004139134,0.0005880724,0.0008951839,0.004917704,0.0002718014,0.002427758,0.001743025,0.001670699,0.2622907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001379928,"about_ca_system_score_gemma":0.001740087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.027274,"about_ca_topic_score_gemma":0.03238901,"domain_scores_codex":[0.9993392,0.00005859569,0.00007350022,0.000135435,0.0002576534,0.000135546],"domain_scores_gemma":[0.9979863,0.0002248276,0.0001509908,0.0004660589,0.001004128,0.0001677661],"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":[0.00003921028,0.000008476698,0.0003890057,0.0001075864,0.00000686771,0.00001327539,0.00001280881,0.0001929284,0.0001091916,0.0004712633,0.9961914,0.002457961],"study_design_scores_gemma":[0.00007651182,0.000006004482,0.002540577,0.00008555109,0.000005868063,0.00002321605,0.00007065026,0.0002584854,0.0003737096,0.001180281,0.9953609,0.00001831153],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002102124,0.00002399127,0.0003069529,0.0001497538,0.0001388296,0.00001903457,0.9925157,0.001677204,0.004958299],"genre_scores_gemma":[0.0008986137,0.00004100072,0.001065808,0.00009489099,0.0000257606,0.00005362184,0.9928155,0.0009823915,0.004022415],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.25982,"threshold_uncertainty_score":0.8691846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06125781128292247,"score_gpt":0.2736980436262981,"score_spread":0.2124402323433757,"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."}}