{"id":"W2799605871","doi":"10.1186/s12880-018-0250-z","title":"Dental age estimation in southern Chinese population using panoramic radiographs: validation of three population specific reference datasets","year":2018,"lang":"en","type":"article","venue":"BMC Medical Imaging","topic":"Forensic Anthropology and Bioarchaeology Studies","field":"Arts and Humanities","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Confidence interval; Medicine; Age groups; Demography; Estimation; Population; Chinese population; Significant difference; Reference values; Mean difference; Dentistry; Orthodontics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005158368,0.000488358,0.000363944,0.00130869,0.0004741656,0.0005304551,0.0006344413,0.0004458056,0.0006958768],"category_scores_gemma":[0.006320836,0.0001399024,0.0004856752,0.001104388,0.0003637238,0.0002843241,0.0006290615,0.0002252189,0.0001960577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000627394,"about_ca_system_score_gemma":0.0009085654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04429477,"about_ca_topic_score_gemma":0.05256925,"domain_scores_codex":[0.9985114,0.0004223032,0.0001787735,0.0003349345,0.0004807126,0.00007181054],"domain_scores_gemma":[0.9968159,0.0004596096,0.0005160982,0.0006900353,0.001415024,0.0001034252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004245022,0.00007805314,0.9591697,0.0001603828,0.0002415,0.0001668025,0.001386719,0.001342253,0.007283553,0.0001550999,0.0003280849,0.02926333],"study_design_scores_gemma":[0.00001226252,0.0001235486,0.9960144,0.00001718437,0.00007435113,0.0002149973,0.0003818448,0.001109614,0.001273996,0.00002987726,0.0007368769,0.00001118431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967,0.00024538,0.001574134,0.00001606034,0.000008078739,0.00004896419,0.0007880545,0.00002432903,0.0005950806],"genre_scores_gemma":[0.9937227,0.0001597048,0.003426583,0.00001464018,0.000008806308,0.00007371195,0.00235332,0.000006458741,0.0002339949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04429477,"threshold_uncertainty_score":0.08807391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05093710642457559,"score_gpt":0.3179184450607743,"score_spread":0.2669813386361987,"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."}}