{"id":"W4310951147","doi":"10.1007/s00784-022-04819-w","title":"An application framework of 3D assessment image registration accuracy and untouched surface area in canal instrumentation laboratory research with micro-computed tomography","year":2022,"lang":"en","type":"article","venue":"Clinical Oral Investigations","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Instrumentation (computer programming); Image registration; Computer science; Artificial intelligence; Computer vision; Software; Measure (data warehouse); Computed tomography; Medicine; Data mining; Radiology; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001945937,0.0001332967,0.0002443476,0.0003138773,0.0003640862,0.000126207,0.0002586575,0.00008878096,0.00004752396],"category_scores_gemma":[0.0002475956,0.0001423994,0.00005107669,0.002477857,0.0008048911,0.0006457231,0.0000824759,0.0009081922,0.000001950856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000107621,"about_ca_system_score_gemma":0.0003355003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001198248,"about_ca_topic_score_gemma":0.0009882959,"domain_scores_codex":[0.9969893,0.001017646,0.00075917,0.0004749168,0.0005333953,0.0002255588],"domain_scores_gemma":[0.9980681,0.0006984742,0.0003595954,0.0004251866,0.0002677675,0.0001809085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006878571,0.000552964,0.9685331,0.00003338018,0.00004154528,0.0000129725,0.0002723911,0.0007210592,0.02281384,0.005112421,0.0004018931,0.001435628],"study_design_scores_gemma":[0.0009527301,0.0004323933,0.9746659,0.00006403728,0.00003909815,0.000009869541,0.00179091,0.0123253,0.001879504,0.007389855,0.0002532451,0.000197198],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926398,0.0000622379,0.005764925,0.000488027,0.0001213976,0.0005476064,0.0001515352,0.00004556419,0.0001789415],"genre_scores_gemma":[0.9179449,0.000009113624,0.08129039,0.0001954413,0.00003255638,0.00008967801,0.0004144629,0.0000164349,0.000006995213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07552547,"threshold_uncertainty_score":0.580688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07778264132366396,"score_gpt":0.4297007758431337,"score_spread":0.3519181345194697,"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."}}