{"id":"W6907461271","doi":"10.20383/102.0707","title":"Impact of adjusted and non-adjusted surface observations on the cold season performance of the Canadian Precipitation Analysis (CaPA) System","year":2023,"lang":"en","type":"dataset","venue":"Federated Research Data Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Precipitation; Winter season; Climate change; Wind speed; Cold climate","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","sts"],"consensus_categories":[],"category_scores_codex":[0.006632242,0.0005721582,0.0009966096,0.001513767,0.003060673,0.0007763017,0.003602763,0.0006939484,0.00001482838],"category_scores_gemma":[0.002493015,0.0003638227,0.0002512835,0.01052235,0.0008063641,0.0005789332,0.001161478,0.002258964,0.0001849293],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002753298,"about_ca_system_score_gemma":0.007181688,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7597629,"about_ca_topic_score_gemma":0.6977556,"domain_scores_codex":[0.9889975,0.004280633,0.001183351,0.001238344,0.003259646,0.00104059],"domain_scores_gemma":[0.9866704,0.00230939,0.001126605,0.005894018,0.003529168,0.0004704074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002775923,0.0001146409,0.01342048,0.0008890308,0.003534637,0.0000254315,0.00008508437,0.006872023,0.004970975,0.00000668784,0.9698005,0.000002874208],"study_design_scores_gemma":[0.0007932077,0.0006455486,0.8046874,0.002747639,0.002382411,0.0000234272,0.00113203,0.1774174,0.001826307,3.169568e-7,0.007709885,0.0006344784],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3507865,0.0001042969,2.592338e-7,0.00007876179,0.0002044763,0.001857018,0.6468416,0.00004097204,0.00008612774],"genre_scores_gemma":[0.4328631,0.00007408026,0.000007193633,0.000003871227,0.00006667125,0.00007722052,0.5664805,0.0000747105,0.0003526972],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9620907,"threshold_uncertainty_score":0.9998814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1673597034528075,"score_gpt":0.3634442202131914,"score_spread":0.1960845167603839,"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."}}