{"id":"W3026454188","doi":"10.3390/app10103513","title":"Digital Design of Minimally Invasive Endodontic Access Cavity","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Endodontics and Root Canal Treatments","field":"Dentistry","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dentin; Cone beam computed tomography; Orthodontics; Dentistry; Computer science; Computed tomography; Medicine; Surgery","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":[0.0005058928,0.0002995412,0.0002585521,0.0005807177,0.0002179374,0.0006105286,0.00065731,0.0004826459,0.001695751],"category_scores_gemma":[0.0009232576,0.0003515918,0.000264012,0.0002590281,0.000493962,0.0005553389,0.0004894587,0.0002974909,0.0004155859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002745018,"about_ca_system_score_gemma":0.0005485219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001824534,"about_ca_topic_score_gemma":0.0003505236,"domain_scores_codex":[0.9995483,0.00004320062,0.00005555699,0.0001150367,0.0002017493,0.00003627989],"domain_scores_gemma":[0.9994829,0.0001328088,0.00008999836,0.00009896318,0.0001460533,0.00004927757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003330747,0.00007490283,0.004954643,0.0008029738,0.0000221149,0.0004174956,0.0003001544,0.006854297,0.7824041,0.007813142,0.0009561606,0.195067],"study_design_scores_gemma":[0.0002252155,0.00444013,0.05697953,0.0001825195,0.0002446568,0.01648339,0.0003637128,0.08737163,0.6638724,0.004314049,0.1651818,0.0003409754],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3506987,0.003169815,0.6367154,0.0001673894,0.0002529322,0.0006022386,0.000337255,0.001118249,0.006938004],"genre_scores_gemma":[0.6417505,0.0007886339,0.3532428,0.00007479275,0.00003058974,0.0003157374,0.0001781625,0.00005928618,0.003559489],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001695751,"threshold_uncertainty_score":0.005672872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08839521697422971,"score_gpt":0.3057782906943415,"score_spread":0.2173830737201118,"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."}}