{"id":"W7100458752","doi":"","title":"Measurement of Precipitation at AWS in Canada: Configuration, Challenges and Alternative Approaches","year":2015,"lang":"en","type":"article","venue":"","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Precipitation; Quantitative precipitation estimation; Climate change; Quantitative precipitation forecast; Weather modification; Plan (archaeology)","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":[],"consensus_categories":[],"category_scores_codex":[0.0006203867,0.00006283912,0.0001164384,0.00006448675,0.00001887467,0.000006488379,0.00005341084,0.00001476982,0.0001168925],"category_scores_gemma":[0.00007956783,0.00005033924,0.00001069573,0.00007006832,0.0000197538,0.0001372668,0.000003852416,0.00002542247,0.000005175808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005463189,"about_ca_system_score_gemma":0.0002479397,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5509555,"about_ca_topic_score_gemma":0.9951181,"domain_scores_codex":[0.9990069,0.00009200076,0.0001886746,0.0001315671,0.0004931926,0.00008761967],"domain_scores_gemma":[0.9996242,0.00003217334,0.00007961149,0.000056638,0.0001354705,0.00007192573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000064942,0.00001963997,0.891517,0.00003792298,0.00006992173,0.000001448116,0.004467307,0.0107581,0.00008372224,0.0005953828,0.000378874,0.09200571],"study_design_scores_gemma":[0.0004117862,0.00004388326,0.9743309,0.00001672834,0.00001276747,4.506111e-7,0.004102371,0.01880768,0.00133784,0.0006503626,0.0001922553,0.00009299137],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.94035,0.007640582,0.0002480947,0.001063621,0.0001083468,0.0001945892,0.000009438759,0.000007744145,0.05037761],"genre_scores_gemma":[0.9995503,0.0001479554,0.0001816923,0.00002113059,0.00001387344,0.000001517353,0.00001924634,8.93776e-7,0.00006342964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4441625,"threshold_uncertainty_score":0.4520347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1644470638894112,"score_gpt":0.2204716690486562,"score_spread":0.05602460515924498,"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."}}