{"id":"W2363119134","doi":"","title":"Dental age assessment using Demirjian′s method on urumqi juveniles","year":2014,"lang":"en","type":"article","venue":"Chinese Journal of Aesthetic Medicine","topic":"Dental Education, Practice, Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Logistic regression; Medicine; Dentistry; Significant difference; Age groups; Demography; Population; Orthodontics; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009619715,0.0002708308,0.0007361466,0.0005352857,0.000504292,0.00001636982,0.00048066,0.0001581257,0.001438874],"category_scores_gemma":[0.00306749,0.0001602621,0.0001344316,0.0004537866,0.0001844364,0.0002417877,0.00009655592,0.001815907,0.0001200003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005719991,"about_ca_system_score_gemma":0.0007599855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002183166,"about_ca_topic_score_gemma":0.00002752373,"domain_scores_codex":[0.9944864,0.002168777,0.001281851,0.0002337509,0.001337085,0.0004921391],"domain_scores_gemma":[0.996025,0.001328062,0.001198575,0.0004423775,0.0004725932,0.0005333612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007244764,0.00116321,0.891194,0.0004966149,0.0001573772,0.000416915,0.01362519,0.0002419203,0.01308196,0.003914752,0.01110816,0.06387543],"study_design_scores_gemma":[0.01174522,0.003808676,0.8554833,0.00408076,0.0004413596,0.004351594,0.02035257,0.005559543,0.0000894319,0.0125117,0.08094417,0.0006316755],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9660457,0.0003740536,0.007717331,0.009943503,0.002700316,0.0003970008,0.000001547203,0.00001975602,0.01280079],"genre_scores_gemma":[0.9837037,0.0001422725,0.009702293,0.003030438,0.001986566,0.00001137031,0.000007089686,0.00005970983,0.001356595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06983601,"threshold_uncertainty_score":0.9994739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09230725869769173,"score_gpt":0.5724339461670794,"score_spread":0.4801266874693877,"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."}}