{"id":"W4394059559","doi":"10.5281/zenodo.7647943","title":"SuperDARN Grid data in netCDF format (2014-Oct)","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; Grid cell; Database; Computer graphics (images); 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":[0.0008531027,0.001111204,0.0008989846,0.002718311,0.0008414444,0.002741793,0.002016919,0.001419474,0.2748278],"category_scores_gemma":[0.004523211,0.0007016115,0.001028769,0.004753122,0.0003031875,0.002553265,0.001925036,0.001850988,0.2625831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001318021,"about_ca_system_score_gemma":0.00181284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02516878,"about_ca_topic_score_gemma":0.03023214,"domain_scores_codex":[0.9992771,0.00006410258,0.0000780509,0.0001472643,0.0002906807,0.0001429449],"domain_scores_gemma":[0.9979616,0.0002354538,0.0001356672,0.000497796,0.001005128,0.0001644046],"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":[0.00004073676,0.00001052863,0.0004486096,0.000119801,0.000008935256,0.00001636045,0.00001592535,0.0002469868,0.0001357041,0.0005608625,0.995518,0.002877577],"study_design_scores_gemma":[0.00007953021,0.000006167392,0.00241745,0.00009155242,0.000007365601,0.00002604751,0.00007417945,0.0003375967,0.000517989,0.00159215,0.9948288,0.00002125393],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000255784,0.00002973286,0.0005923095,0.0001491124,0.000152637,0.00002875875,0.9897581,0.002741412,0.006292133],"genre_scores_gemma":[0.001048419,0.00004606244,0.001551046,0.00009444804,0.00002777337,0.0000685116,0.9914604,0.001504909,0.004198503],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2748278,"threshold_uncertainty_score":0.9193906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06119512835865625,"score_gpt":0.2745917254346735,"score_spread":0.2133965970760173,"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."}}