{"id":"W2889203207","doi":"10.1175/bams-d-17-0200.1","title":"The Community Foehn Classification Experiment","year":2018,"lang":"en","type":"article","venue":"Bulletin of the American Meteorological Society","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Terrain; Classifier (UML); Computer science; Meteorology; Climatology; Environmental science; Artificial intelligence; Geography; Geology; Cartography","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":["sts","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.001357899,0.0001293599,0.0002215233,0.000005847402,0.001564639,0.00003479524,0.0008909469,0.00005322705,0.002288322],"category_scores_gemma":[0.0004299767,0.0000567253,0.0002716888,0.0002641666,0.003269166,0.00001280596,0.00009668823,0.0003352525,0.0001723258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008625561,"about_ca_system_score_gemma":0.00001516233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001238652,"about_ca_topic_score_gemma":0.00007666047,"domain_scores_codex":[0.9978095,0.001100478,0.0003065205,0.0001785757,0.0002992926,0.0003056274],"domain_scores_gemma":[0.9972849,0.001649611,0.0003305467,0.0005675823,0.00008318995,0.00008412526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001222844,0.0007292521,0.4790058,0.00002320614,0.0005272429,8.778849e-7,0.003025655,0.001795561,0.01103199,0.01001088,0.1607431,0.3318835],"study_design_scores_gemma":[0.0001407882,0.0007609616,0.8672827,0.000002053067,0.00001954482,0.000001061226,0.001272916,0.002049487,0.0002861175,0.004335704,0.1237406,0.0001080642],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796488,0.0002282084,0.0002033282,0.007551174,0.0001565214,0.0002121639,0.00001490024,0.00004016589,0.0119447],"genre_scores_gemma":[0.993522,0.0000608544,0.002583775,0.003414869,0.0001104484,0.000005330783,0.000006006443,0.000002520627,0.0002941297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3882768,"threshold_uncertainty_score":0.9997352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04387578073795704,"score_gpt":0.2668623643199806,"score_spread":0.2229865835820235,"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."}}