{"id":"W3199640011","doi":"10.1155/2021/2673040","title":"Comparison of Accuracy of Current Ten Intraoral Scanners","year":2021,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Dental materials and restorations","field":"Dentistry","cited_by":171,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Materials Research; Prince of Songkla University","keywords":"Current (fluid); Computer science; Orthodontics; Dentistry; Medicine; Geology","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":[0.005439619,0.0005707711,0.0005919845,0.002654179,0.0005525002,0.00196054,0.001264914,0.001409551,0.002924511],"category_scores_gemma":[0.01394675,0.0006270888,0.0007127153,0.00160759,0.0007194449,0.001248258,0.001361945,0.0006731533,0.001119301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000903019,"about_ca_system_score_gemma":0.001006255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002365456,"about_ca_topic_score_gemma":0.004587051,"domain_scores_codex":[0.9933867,0.000947095,0.000672215,0.001211083,0.003522089,0.0002609317],"domain_scores_gemma":[0.9874549,0.003319878,0.0009303371,0.001748154,0.006286112,0.0002606693],"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":[0.002945791,0.0001698203,0.2771405,0.001322178,0.0004884889,0.0003324923,0.00249661,0.003322204,0.1149598,0.001957951,0.004066661,0.5907975],"study_design_scores_gemma":[0.0001531361,0.002391624,0.6956545,0.0008294769,0.001577168,0.01013827,0.003672559,0.03347451,0.1935824,0.001636238,0.0564282,0.0004619719],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8956038,0.01517629,0.07029359,0.0006934368,0.0005010965,0.0001301785,0.001371945,0.001934055,0.0142956],"genre_scores_gemma":[0.9153324,0.002790892,0.07664919,0.0001941858,0.00007306488,0.00005757851,0.001044045,0.0002273972,0.003631203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005439619,"threshold_uncertainty_score":0.02876782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2249711726583307,"score_gpt":0.5392742285280243,"score_spread":0.3143030558696935,"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."}}