{"id":"W4399543985","doi":"10.1175/bams-d-23-0056.1","title":"Effective Visualization of Radar Data for Users Impacted by Color Vision Deficiency","year":2024,"lang":"en","type":"article","venue":"Bulletin of the American Meteorological Society","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Radar; Storm; Mesoscale meteorology; Weather radar; Doppler radar; Interpretability; Meteorology; Computer science; Reflectivity; Remote sensing; Environmental science; Geography; Artificial intelligence; Optics; Telecommunications; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002711209,0.001544284,0.000747961,0.002750397,0.0008472871,0.003459808,0.001310807,0.000891729,0.02502945],"category_scores_gemma":[0.01479472,0.00055246,0.0009728636,0.001327311,0.0004774384,0.003030767,0.00455924,0.00141838,0.006035181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006272063,"about_ca_system_score_gemma":0.000834817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003273706,"about_ca_topic_score_gemma":0.003906786,"domain_scores_codex":[0.9988757,0.0004394008,0.00008580481,0.0001441094,0.0003342904,0.0001207533],"domain_scores_gemma":[0.9909393,0.004385021,0.0004080919,0.001490254,0.00201663,0.0007607273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001749685,0.0003356964,0.0209431,0.002052486,0.0001838917,0.002620411,0.01023595,0.008174876,0.03193636,0.009460945,0.5096332,0.4026734],"study_design_scores_gemma":[0.0004647269,0.0003746877,0.03448337,0.001310241,0.0002298085,0.0023013,0.005949559,0.1891363,0.04907696,0.03369908,0.682394,0.0005799084],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1114958,0.001776685,0.4237312,0.007198161,0.001503068,0.0008729046,0.02672251,0.3907471,0.03595258],"genre_scores_gemma":[0.4483198,0.001550311,0.4793359,0.002254872,0.0005236448,0.0007329066,0.01986232,0.03346961,0.01395066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02502945,"threshold_uncertainty_score":0.08373183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008964836545967454,"score_gpt":0.2724486894339667,"score_spread":0.2634838528879992,"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."}}