{"id":"W4391578484","doi":"10.1080/09540091.2024.2306962","title":"AICOM-MP: an AI-based monkeypox detector for resource-constrained environments","year":2024,"lang":"en","type":"article","venue":"Connection Science","topic":"Poxvirus research and outbreaks","field":"Immunology and Microbiology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Monkeypox; Computer science; Detector; Artificial intelligence; Telecommunications; Vaccinia; Chemistry","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":[0.0008430512,0.001351249,0.00100896,0.00272527,0.0005046536,0.001475302,0.001769947,0.001634686,0.007548633],"category_scores_gemma":[0.003031975,0.0003889259,0.001030089,0.001412631,0.0002873506,0.001440086,0.001990674,0.0009053081,0.006220629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000658313,"about_ca_system_score_gemma":0.0008665849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005560876,"about_ca_topic_score_gemma":0.009855466,"domain_scores_codex":[0.9992946,0.00009665047,0.00004089169,0.0002075562,0.0002477758,0.0001125329],"domain_scores_gemma":[0.9991974,0.0002398694,0.00008170187,0.0001479462,0.0002253388,0.000107664],"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":[0.001690037,0.0006321123,0.04794151,0.00226178,0.0006966968,0.000932495,0.0003302701,0.02110674,0.04942205,0.003527381,0.4956562,0.3758026],"study_design_scores_gemma":[0.0003236887,0.0006520524,0.06065008,0.0003458359,0.000229437,0.002280765,0.0006330948,0.6705235,0.0579098,0.01083418,0.1954031,0.0002143948],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2153062,0.005368288,0.3278166,0.002016925,0.001735741,0.002858393,0.1912552,0.2093857,0.04425699],"genre_scores_gemma":[0.2734112,0.001106916,0.4182873,0.001413883,0.0003354782,0.001474216,0.290133,0.003094467,0.01074352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007548633,"threshold_uncertainty_score":0.0252527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02746600345583997,"score_gpt":0.308521640929578,"score_spread":0.2810556374737381,"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."}}