{"id":"W2160396818","doi":"10.1109/gmai.2008.14","title":"Chapter 8: Sketching Expressive Visualization of a Natural Phenomenon: Ultra-violet Individual Exposure Estimation","year":2008,"lang":"en","type":"article","venue":"","topic":"Skin Protection and Aging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health","funders":"Université de Genève","keywords":"Rendering (computer graphics); Sketch; Computer science; Visualization; Computer vision; Artificial intelligence; Sun exposure; Clothing; Computer graphics (images); Human–computer interaction; Algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.00009371945,0.00009498049,0.0001555741,0.0001316471,0.000090462,0.000007859188,0.00003948388,0.00004789756,0.0003242474],"category_scores_gemma":[0.00007450431,0.00007718773,0.00004569035,0.0001215196,0.00004118296,0.000154653,0.00001257457,0.0001092728,0.00001056394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001803825,"about_ca_system_score_gemma":0.00002043856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001479203,"about_ca_topic_score_gemma":6.288032e-7,"domain_scores_codex":[0.9992374,0.00002165974,0.0002255741,0.0001479424,0.0002583563,0.000109134],"domain_scores_gemma":[0.9996162,0.00002729675,0.0001105213,0.0001111815,0.00008727083,0.00004753359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001020498,0.0008847803,0.07435537,0.0005979516,0.0005495112,0.0001713692,0.05714069,0.001108353,0.6915982,0.02556287,0.001402568,0.1456078],"study_design_scores_gemma":[0.009448881,0.001351184,0.1472549,0.001108273,0.0002306429,0.001489448,0.003464855,0.02292804,0.8097075,0.001021798,0.001195436,0.0007990067],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9559462,0.0001649984,0.03531338,0.0001938216,0.0001621811,0.0003391442,0.000002090477,0.0001167352,0.007761469],"genre_scores_gemma":[0.9959617,0.00001477697,0.003076921,0.0003517822,0.00008893319,0.00001162498,0.00003840249,0.00001265725,0.000443164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1448088,"threshold_uncertainty_score":0.3550282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02335383207553495,"score_gpt":0.2798150326428921,"score_spread":0.2564612005673572,"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."}}