{"id":"W6968127575","doi":"10.5281/zenodo.12625645","title":"Elderly Population Improve Quality of Oral Life","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Dental Health and Care Utilization","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"CARE Canada","funders":"","keywords":"Oral health; Quality of life (healthcare); Elderly people; Population; Population ageing; Geriatrics; Aged population; Quality (philosophy)","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":[0.00109028,0.0002181166,0.0003621172,0.0005957337,0.0004813427,0.0006426182,0.0002368529,0.0003834542,0.01313137],"category_scores_gemma":[0.002832042,0.00004838932,0.0003701589,0.0003969935,0.0001107389,0.0003336549,0.0009016826,0.0004293334,0.001379523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003950131,"about_ca_system_score_gemma":0.0007082435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003032684,"about_ca_topic_score_gemma":0.004791612,"domain_scores_codex":[0.9995112,0.0001628476,0.00003328462,0.00004338332,0.0001349994,0.0001142541],"domain_scores_gemma":[0.999315,0.00006432131,0.0001765803,0.00003788633,0.0002324691,0.0001738172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003245321,0.003027937,0.2854582,0.00126926,0.0002128153,0.0002475091,0.001032369,0.0002063028,0.001311189,0.001017999,0.06863023,0.6372616],"study_design_scores_gemma":[0.0001902897,0.00235947,0.8918087,0.00114463,0.000310967,0.000698899,0.002521921,0.0003815866,0.0009811752,0.001293222,0.09828771,0.00002147406],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8519377,0.03347839,0.001983166,0.02477376,0.001133458,0.0004411424,0.003921939,0.000347201,0.08198313],"genre_scores_gemma":[0.9704204,0.01023398,0.002706295,0.003300793,0.0004626787,0.0002026549,0.001230816,0.0000130321,0.01142931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01313137,"threshold_uncertainty_score":0.04392886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07416934691357906,"score_gpt":0.3428914792743323,"score_spread":0.2687221323607533,"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."}}