{"id":"W1565304112","doi":"10.1002/jgrd.50323","title":"Multisegment statistical bias correction of daily GCM precipitation output","year":2013,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Climate variability and models","field":"Environmental Science","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Quantile; Precipitation; Estimator; Cumulative distribution function; Forcing (mathematics); Statistics; Function (biology); Mathematics; Probability density function; Meteorology; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00115872,0.0001020717,0.0002485749,0.00001569178,0.0001015822,0.00005683783,0.0002669835,0.00006538371,0.003348188],"category_scores_gemma":[0.0017094,0.00007712117,0.0001009311,0.000270087,0.000411908,0.0004704059,0.0001784822,0.0004420753,0.0005048007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002386527,"about_ca_system_score_gemma":0.00005823898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004296374,"about_ca_topic_score_gemma":0.00009079249,"domain_scores_codex":[0.9972082,0.0003988226,0.0005208928,0.0001851112,0.001339131,0.0003478549],"domain_scores_gemma":[0.9976085,0.00148677,0.0002105629,0.0001943624,0.000247742,0.0002520912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001274299,0.005401069,0.0740429,0.000174589,0.0001937647,0.00003872491,0.004687581,0.04341974,0.1565056,0.001541346,0.1595547,0.5531657],"study_design_scores_gemma":[0.001250417,0.003006991,0.7777848,0.0001379274,0.00003312353,0.00001113869,0.001098806,0.1732852,0.005758407,0.03449817,0.002902182,0.000232764],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993264,0.00001879715,0.003511279,0.0002793124,0.0002095171,0.0002724068,0.000005764114,0.000005967247,0.002432926],"genre_scores_gemma":[0.9914889,0.00004303364,0.007357497,0.00001888493,0.00009933398,0.00001285158,0.000002213239,0.00001045827,0.0009667878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7037419,"threshold_uncertainty_score":0.9975629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06024390106151724,"score_gpt":0.333266287558607,"score_spread":0.2730223864970898,"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."}}