{"id":"W4381716203","doi":"10.1111/exd.14863","title":"Skin microbiome attributes associate with biophysical skin ageing","year":2023,"lang":"en","type":"article","venue":"Experimental Dermatology","topic":"Dermatology and Skin Diseases","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pan Am Clinic","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of General Medical Sciences; National Cancer Institute; National Institute on Aging; National Institutes of Health","keywords":"Microbiome; Metagenomics; Ageing; Shotgun; Biology; Skin Aging; Computational biology; Genetics; Gene; Medicine; Dermatology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004316762,0.000250771,0.0005447573,0.0002125221,0.0001770929,0.0000203093,0.0001342803,0.00018767,0.0002262049],"category_scores_gemma":[0.00002540415,0.0002103578,0.0001502041,0.0004742506,0.0003417048,0.0001023767,0.0001203138,0.0001870147,0.00163816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000633478,"about_ca_system_score_gemma":0.00006607563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001694639,"about_ca_topic_score_gemma":0.000002774263,"domain_scores_codex":[0.9984798,0.0001024031,0.0002764933,0.0003877289,0.000173335,0.0005802173],"domain_scores_gemma":[0.9993021,0.000115774,0.00008401267,0.0002732897,0.00003814847,0.0001866363],"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":[0.001167436,0.00215491,0.1295539,0.0002492693,0.001059461,0.03211558,0.002388218,0.000005654694,0.4661026,0.001478186,0.3632026,0.0005221543],"study_design_scores_gemma":[0.003441645,0.0001579892,0.1030095,0.00008266928,0.0000939463,0.00600979,0.001031104,0.0001715777,0.8748999,0.00008273108,0.01064326,0.0003758805],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939214,0.0006925898,0.00001747626,0.002344876,0.0002225798,0.0002767602,0.00002705147,0.0003951087,0.002102168],"genre_scores_gemma":[0.9975005,0.00001484641,0.0001630412,0.001162584,0.000073574,0.00008061689,0.0003163995,0.00004001512,0.0006483907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4087973,"threshold_uncertainty_score":0.9991392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373072421772157,"score_gpt":0.2856987285784055,"score_spread":0.2719680043606839,"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."}}