{"id":"W7066126095","doi":"","title":"The French Canadian dataset of Demirjian for dental age estimation: a systematic and meta-analysis","year":2013,"lang":"en","type":"article","venue":"The HKU Scholars Hub (University of Hong Kong)","topic":"Forensic Anthropology and Bioarchaeology Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"MEDLINE; Edentulism; Population; Epidemiology; Age groups","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":["metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.01516752,0.002196643,0.003749772,0.01040778,0.002992093,0.00236046,0.003898873,0.001670241,0.006803883],"category_scores_gemma":[0.03930224,0.001084563,0.007596776,0.02146744,0.0006992555,0.0006335441,0.001791365,0.001179949,0.0005938669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01530947,"about_ca_system_score_gemma":0.03822391,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9190239,"about_ca_topic_score_gemma":0.9584773,"domain_scores_codex":[0.9905647,0.002805451,0.00174762,0.001761137,0.002325354,0.0007957319],"domain_scores_gemma":[0.9774884,0.005355685,0.002787726,0.002994737,0.01055892,0.0008145518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.005634578,0.0001757353,0.5159055,0.04173915,0.2094204,0.0007461379,0.001830641,0.001881294,0.001034953,0.002278148,0.1387788,0.08057463],"study_design_scores_gemma":[0.001986827,0.0001507721,0.7448474,0.008926164,0.1464229,0.0006024021,0.001184039,0.0008410139,0.0005478054,0.0006731294,0.09347014,0.0003473589],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.200543,0.2884471,0.007915912,0.00278628,0.0009748393,0.002191444,0.4879746,0.0003843131,0.008782455],"genre_scores_gemma":[0.7357817,0.05250275,0.01850606,0.003347525,0.0002851836,0.005059802,0.1790362,0.0003754882,0.005105294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9962502,"threshold_uncertainty_score":0.1629059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04625721142662095,"score_gpt":0.2344532343548544,"score_spread":0.1881960229282334,"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."}}