{"id":"W206328681","doi":"","title":"Cerec: correlation, an accurate and practical method for occlusal reconstruction.","year":2001,"lang":"en","type":"article","venue":"PubMed","topic":"Temporomandibular Joint Disorders","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"CEREC; Correlation; Computer science; Orthodontics; Mathematics; Materials science; Medicine; Geometry; Ceramic; Composite material","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":[0.002345935,0.001041889,0.0009279073,0.003713731,0.0009330528,0.001080679,0.001010578,0.001609317,0.01764476],"category_scores_gemma":[0.004944951,0.0006385682,0.0005943559,0.00194058,0.001113174,0.001531492,0.002223632,0.002109874,0.007733211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003106283,"about_ca_system_score_gemma":0.001520701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001264098,"about_ca_topic_score_gemma":0.002093527,"domain_scores_codex":[0.9978853,0.0004822534,0.0001424784,0.0002868259,0.001059302,0.0001437464],"domain_scores_gemma":[0.9985544,0.0005752937,0.0002120878,0.000291148,0.0002673146,0.00009969062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001085722,0.00009378143,0.00446491,0.001183971,0.00008178873,0.004193245,0.0003906777,0.0003725849,0.0597475,0.008259269,0.05689933,0.8632271],"study_design_scores_gemma":[0.0004510999,0.00141116,0.03496937,0.001531972,0.0002978545,0.2669714,0.0007313045,0.008373951,0.08282442,0.007566922,0.5944588,0.0004116083],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04149878,0.07118694,0.7735468,0.004082046,0.006325949,0.001177,0.002585846,0.01312764,0.08646902],"genre_scores_gemma":[0.2054949,0.02317811,0.7137926,0.002014594,0.001747393,0.001007787,0.002338136,0.001748452,0.04867801],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01764476,"threshold_uncertainty_score":0.05902761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.114992357746737,"score_gpt":0.4436533443282355,"score_spread":0.3286609865814986,"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."}}