{"id":"W2989888358","doi":"","title":"Identifying optimal physical parameterizations combination for WRF for regional climate studies over Southern Ontario","year":2013,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climatology; Weather Research and Forecasting Model; Climate model; Environmental science; Meteorology; Climate change; Geography; Geology; Oceanography","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":[0.0007707906,0.0004037367,0.000382093,0.0009987017,0.001059268,0.001213868,0.0007458313,0.0005819729,0.001984798],"category_scores_gemma":[0.003340788,0.0003700652,0.0007398394,0.001207323,0.0003084298,0.0009653622,0.0004911117,0.0003691363,0.0002272153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004069948,"about_ca_system_score_gemma":0.005997421,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7643112,"about_ca_topic_score_gemma":0.8727028,"domain_scores_codex":[0.9997078,0.00005842398,0.00001512301,0.00009215264,0.00004550854,0.00008102745],"domain_scores_gemma":[0.9993927,0.0001673082,0.00006189405,0.0000843326,0.0002338697,0.00005975379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000358105,0.0001451566,0.3057362,0.0002318685,0.0003780714,0.0003195452,0.0005920547,0.5296525,0.01283753,0.002611224,0.006665595,0.1404723],"study_design_scores_gemma":[0.0001048624,0.00003948229,0.3088656,0.00004828838,0.000159486,0.00003763459,0.001140926,0.6789219,0.003368543,0.001862806,0.005384404,0.00006617459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9647748,0.0003299404,0.02247064,0.0005611968,0.00002097028,0.0001140407,0.005201091,0.0004934911,0.006033799],"genre_scores_gemma":[0.9813664,0.00008741838,0.01560279,0.00002453928,0.000006866428,0.00003541476,0.001962607,0.00007193735,0.0008420179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2356888,"threshold_uncertainty_score":0.4741536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06630952860138437,"score_gpt":0.3020912110599157,"score_spread":0.2357816824585313,"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."}}