{"id":"W6917541300","doi":"10.57757/iugg23-0746","title":"Observed precipitation trends inferred from Canada’s homogenized monthly precipitation dataset","year":2023,"lang":"en","type":"article","venue":"IUGG 2023","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Homogenization (climate); Precipitation; Quantile; Data series; Trend analysis; Homogeneity (statistics); Time series; Series (stratigraphy)","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":[0.000489539,0.0003328479,0.0002336287,0.002122485,0.0007697986,0.0009907547,0.0006505402,0.0001968681,0.001719913],"category_scores_gemma":[0.00279384,0.0002477794,0.0003880208,0.005330516,0.0002544047,0.0003457605,0.0003973944,0.000342174,0.0005757965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009347872,"about_ca_system_score_gemma":0.01387599,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9827096,"about_ca_topic_score_gemma":0.9890447,"domain_scores_codex":[0.9995597,0.00002487801,0.00002961872,0.0000844344,0.0002059611,0.00009542485],"domain_scores_gemma":[0.9981397,0.0001146357,0.0001068187,0.0002004458,0.001349372,0.00008901009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003434948,0.00008576123,0.7095829,0.0004285004,0.0005108494,0.0005087777,0.0009580245,0.07504515,0.01068377,0.004755375,0.08721753,0.1098798],"study_design_scores_gemma":[0.00003403869,0.00001367847,0.8736672,0.00006178599,0.00008487825,0.00007163761,0.0004641522,0.06924208,0.003847263,0.0004943773,0.05195779,0.00006105335],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6289673,0.0003497548,0.01003469,0.0005064428,0.00004793562,0.0001389357,0.347119,0.001791251,0.01104493],"genre_scores_gemma":[0.6959199,0.0004125694,0.0176797,0.0001015541,0.00002001876,0.00009992051,0.2816933,0.0001968805,0.003876139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01729035,"threshold_uncertainty_score":0.06782389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02624728552332651,"score_gpt":0.2507356115801249,"score_spread":0.2244883260567984,"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."}}