{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005033866,0.0009944201,0.000849837,0.00118064,0.001244948,0.000995111,0.001908837,0.00253033,0.006275618],"category_scores_gemma":[0.0149919,0.0001987242,0.000657361,0.001106705,0.0006655056,0.002207168,0.001383386,0.001615891,0.003156919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009648041,"about_ca_system_score_gemma":0.0008250606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006287733,"about_ca_topic_score_gemma":0.009248274,"domain_scores_codex":[0.9962757,0.001242168,0.0002058207,0.00109006,0.0008637918,0.0003224954],"domain_scores_gemma":[0.9871759,0.005452604,0.000706255,0.003046291,0.002670686,0.0009483618],"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":[0.01891284,0.02034423,0.1276527,0.0021226,0.0007573482,0.001506023,0.003212083,0.03003911,0.02363441,0.004783955,0.234186,0.5328487],"study_design_scores_gemma":[0.006053585,0.01308542,0.2000589,0.0005490541,0.000451619,0.001598865,0.006294085,0.5393054,0.04305013,0.01325584,0.1758552,0.0004419603],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9588408,0.0006698455,0.00760519,0.00106992,0.0007586135,0.001374129,0.01176441,0.002429081,0.01548788],"genre_scores_gemma":[0.9103482,0.0001944936,0.03011162,0.0006907216,0.0003875282,0.001333209,0.04308132,0.0003620842,0.01349075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006287733,"threshold_uncertainty_score":0.02662194,"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."}}