{"id":"W4387036948","doi":"10.21203/rs.3.rs-3366971/v1","title":"AICOM-MP: an AI-based Monkeypox Detector for Resource-Constrained Environments","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Poxvirus research and outbreaks","field":"Immunology and Microbiology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"McGill University","keywords":"Computer science; Monkeypox; Mobile device; Mobile phone; Artificial intelligence; World Wide Web; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001158155,0.001494747,0.001227413,0.002658276,0.0006316332,0.002068063,0.002101407,0.002164822,0.009144465],"category_scores_gemma":[0.006401846,0.0004552871,0.001269054,0.001500116,0.0003727711,0.00178842,0.002501038,0.001279223,0.007170188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007856229,"about_ca_system_score_gemma":0.001135328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005771071,"about_ca_topic_score_gemma":0.008569335,"domain_scores_codex":[0.998884,0.0001640176,0.00007424702,0.0003283533,0.0003968773,0.000152411],"domain_scores_gemma":[0.9986533,0.0004873133,0.0001203402,0.0002248129,0.0003980246,0.0001162398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001437946,0.0004524339,0.02126462,0.001451531,0.0005202434,0.0009254012,0.0002399948,0.02658482,0.03481019,0.006303894,0.3713995,0.5346094],"study_design_scores_gemma":[0.0001893442,0.0004894066,0.01741212,0.000269286,0.0001603684,0.001727315,0.0003648877,0.7793509,0.04108404,0.01275925,0.1460095,0.0001835637],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1220351,0.006359029,0.6231181,0.002987933,0.002340651,0.002534067,0.07594044,0.1286737,0.03601086],"genre_scores_gemma":[0.2386244,0.001312902,0.6170999,0.002307111,0.0004601633,0.001684787,0.1218337,0.002840496,0.01383654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009144465,"threshold_uncertainty_score":0.03059125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0860306818815361,"score_gpt":0.3840906222334231,"score_spread":0.298059940351887,"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."}}