{"id":"W2887324243","doi":"10.1175/waf-d-18-0033.1","title":"Predicting the Inland Penetration of Long-Lake-Axis-Parallel Snowbands","year":2018,"lang":"en","type":"article","venue":"Weather and Forecasting","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Advection; Boundary layer; Meteorology; Environmental science; Convection; Penetration (warfare); Penetration depth; Mixed layer; Atmospheric sciences; Geology; Climatology; Mechanics; Physics; Mathematics","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":[0.000368818,0.00006649547,0.00009292267,0.00002383201,0.0002671998,0.00003045815,0.00007390593,0.00003617751,0.0007300768],"category_scores_gemma":[0.00008271769,0.00003746216,0.0000237639,0.00009929777,0.000133246,0.00008626084,0.000008728977,0.00006358845,0.000009357387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":5.797233e-7,"about_ca_system_score_gemma":0.000007520227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000142882,"about_ca_topic_score_gemma":0.00110515,"domain_scores_codex":[0.9994123,0.0000459737,0.0001791671,0.00011942,0.0001044631,0.0001386541],"domain_scores_gemma":[0.9995248,0.0002423271,0.00007684107,0.00007997443,0.00003513199,0.00004091576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002218841,0.000003634201,0.9663193,0.000005656715,0.000007667983,4.539628e-7,0.0005745756,0.001284898,0.00001636621,0.00008642839,0.00001390254,0.03166498],"study_design_scores_gemma":[0.0001660265,0.0001983416,0.866444,0.000009126218,0.000009986729,0.000006101014,0.00009322731,0.1310659,0.00001224654,0.001716685,0.0002242107,0.00005418704],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9487284,0.0002068404,0.00163757,0.00005065501,0.00007990646,0.0000901238,0.00001201158,0.00001318225,0.0491813],"genre_scores_gemma":[0.9989239,0.000008118375,0.000561838,0.00006219399,0.0002162075,6.319822e-7,0.00001665241,0.000001753303,0.0002087287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.129781,"threshold_uncertainty_score":0.7993829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04195537676661715,"score_gpt":0.231436292662868,"score_spread":0.1894809158962509,"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."}}