{"id":"W4292493928","doi":"10.1049/syb2.12048","title":"CHAC1 as a novel biomarker for distinguishing alopecia from other dermatological diseases and determining its severity","year":2022,"lang":"en","type":"article","venue":"IET Systems Biology","topic":"Hair Growth and Disorders","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Calgary","funders":"","keywords":"Biomarker; Medicine; Dermatology; Computational biology; Biology; 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":[0.0005895029,0.0004879932,0.0004911122,0.002828816,0.0003166844,0.0008342714,0.0002083441,0.0004799959,0.001813378],"category_scores_gemma":[0.0009092266,0.0001257366,0.0004329333,0.001309954,0.0002722875,0.0003061581,0.0004272505,0.0004712445,0.0002767499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004689817,"about_ca_system_score_gemma":0.0003244247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001281507,"about_ca_topic_score_gemma":0.001876056,"domain_scores_codex":[0.9996337,0.0000739275,0.00002526341,0.0001182545,0.00009968517,0.00004916712],"domain_scores_gemma":[0.9994037,0.0001943946,0.0001806709,0.00003563299,0.0001041053,0.00008154607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00187174,0.0002339889,0.6359274,0.0007545686,0.0006706707,0.0008896483,0.0001562771,0.005703395,0.2569499,0.0007491286,0.001620847,0.09447239],"study_design_scores_gemma":[0.00008028781,0.0006707674,0.887544,0.0001063061,0.0005153882,0.003116455,0.0002861654,0.0497958,0.04951909,0.001873526,0.006435699,0.00005650968],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786163,0.0072075,0.008323752,0.0002048551,0.00004253516,0.0001253191,0.002450331,0.0001561112,0.002873309],"genre_scores_gemma":[0.9938254,0.0006443326,0.003705948,0.00006166259,0.00002372528,0.00004302453,0.001261631,0.000008782098,0.0004255529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002828816,"threshold_uncertainty_score":0.006066382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04651910540445012,"score_gpt":0.3106557001882834,"score_spread":0.2641365947838332,"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."}}