{"id":"W7159034119","doi":"10.14042/j.cnki.32.1309.2022.05.008","title":"An innovative multi-source precipitation merging method with the identification of rain and no rain","year":2022,"lang":"zh","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Precipitation; Quantitative precipitation forecast; Precipitation types; Quantitative precipitation estimation; Rain gauge; Identification (biology); Logistic regression; Linear regression","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001055217,0.0009817245,0.000782215,0.001478347,0.0005508055,0.0006766024,0.001390375,0.0007569939,0.00109067],"category_scores_gemma":[0.001976192,0.0004934199,0.001244393,0.001529931,0.0003106697,0.002093786,0.00145962,0.0008723605,0.0004900012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002952872,"about_ca_system_score_gemma":0.0008895039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003128394,"about_ca_topic_score_gemma":0.00303615,"domain_scores_codex":[0.9993741,0.0000863317,0.00005234624,0.0002193534,0.0002050568,0.0000628798],"domain_scores_gemma":[0.999343,0.0001069573,0.0001112964,0.000103444,0.0002896209,0.00004568079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003793322,0.000187218,0.01836628,0.0002586155,0.0003453536,0.0003267682,0.00058575,0.1066174,0.06627539,0.003963388,0.004315723,0.7983788],"study_design_scores_gemma":[0.00005647715,0.00007778023,0.00732044,0.00001395723,0.0001081067,0.0002055956,0.00007225576,0.9670293,0.01985223,0.001877667,0.003336728,0.00004940619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03744787,0.0001999927,0.9598255,0.0000874758,0.0000734908,0.00006952093,0.0001191618,0.001438142,0.0007389191],"genre_scores_gemma":[0.3963653,0.0002011727,0.5999861,0.0001234051,0.000122917,0.0001386189,0.0007845737,0.0002436001,0.002034433],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003128394,"threshold_uncertainty_score":0.0062204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1880059224962822,"score_gpt":0.4908967525771412,"score_spread":0.302890830080859,"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."}}