{"id":"W6920654667","doi":"10.60692/jgj37-23y02","title":"3D-printed versus conventionally milled zirconia for dental clinical applications: Trueness, precision, accuracy, biological and esthetic aspects.","year":2024,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Dental materials and restorations","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cubic zirconia; Biocompatibility; Dental restoration; Significant difference; Materials testing","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":[0.008874572,0.001075507,0.007878999,0.007084745,0.0004790834,0.003127117,0.001384942,0.002442175,0.003385535],"category_scores_gemma":[0.03275186,0.0007620927,0.007927146,0.005564563,0.000944611,0.001867234,0.001110731,0.0009830474,0.0003132244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002127131,"about_ca_system_score_gemma":0.0045976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002748636,"about_ca_topic_score_gemma":0.00941246,"domain_scores_codex":[0.9891806,0.003405201,0.004735027,0.00065344,0.001883073,0.0001425923],"domain_scores_gemma":[0.9697637,0.02359154,0.004660477,0.0004175189,0.001430613,0.0001361582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004438281,0.00002400601,0.0005351629,0.9389139,0.01184066,0.00007346223,0.000125682,0.00004791168,0.0004996406,0.0002056646,0.0005514467,0.04673871],"study_design_scores_gemma":[0.0009718922,0.001421853,0.00878091,0.778262,0.1760378,0.001082363,0.0004881608,0.0001708416,0.0009882862,0.0006363011,0.0310749,0.00008457126],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.001074801,0.9983594,0.0001036398,0.00007883208,0.0000513635,0.000088078,0.0001179797,0.000002587317,0.0001233552],"genre_scores_gemma":[0.03748065,0.9592243,0.001526487,0.000754753,0.0001213237,0.0004463838,0.0002516524,0.000009503348,0.0001849263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008874572,"threshold_uncertainty_score":0.04693377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0713076841804369,"score_gpt":0.3217970354387267,"score_spread":0.2504893512582899,"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."}}