{"id":"W4313545980","doi":"10.1128/spectrum.04180-22","title":"Sweat and Sebum Preferences of the Human Skin Microbiota","year":2023,"lang":"en","type":"article","venue":"Microbiology Spectrum","topic":"Dermatology and Skin Diseases","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Biology; Microbiome; SWEAT; Human skin; Ecology; Microbial ecology; Context (archaeology); Niche; Microbiology; Bacteria; Zoology; Bioinformatics; Genetics","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":[0.0001563339,0.0001895852,0.0001954845,0.0002410495,0.0001602867,0.0003839197,0.00006952502,0.0002536853,0.0009843685],"category_scores_gemma":[0.0004406105,0.00009929711,0.0001329293,0.0001545955,0.00019606,0.0002115801,0.0003856202,0.0001780384,0.0002044488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006185447,"about_ca_system_score_gemma":0.0001459234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005434285,"about_ca_topic_score_gemma":0.0007337682,"domain_scores_codex":[0.9996877,0.0001223262,0.00002068965,0.00007020143,0.00006405557,0.00003497209],"domain_scores_gemma":[0.9998786,0.00002935922,0.00002724755,0.00000955057,0.00002969037,0.00002544762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003305167,0.00004212846,0.009366398,0.00005997737,0.00000962951,0.00004521474,0.0001060759,0.00005980619,0.9870913,0.00003777177,0.00003006237,0.002821099],"study_design_scores_gemma":[0.00002966581,0.002632605,0.3812511,0.00008982183,0.00007098562,0.001814156,0.002559539,0.00149491,0.6054747,0.000351174,0.004172678,0.00005880012],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998301,0.0005114941,0.0003920653,0.00003282263,0.000006809576,0.00001511141,0.0002001529,0.000003455908,0.0005371401],"genre_scores_gemma":[0.9979537,0.000405413,0.001028913,0.00004808583,0.000006197589,0.00001466032,0.0002144149,0.000003774467,0.0003248802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009843685,"threshold_uncertainty_score":0.003293037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123312512197551,"score_gpt":0.2552524964100041,"score_spread":0.242921245190249,"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."}}