{"id":"W3173215294","doi":"10.3390/app11135850","title":"Computer-Assisted Detection of Cemento-Enamel Junction in Intraoral Ultrasonographs","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; China Scholarship Council; Mitacs; Children's Hospital Foundation; Stollery Children’s Hospital Foundation; Alberta Innovates - Technology Futures; Women and Children's Health Research Institute; Children's Health Research Institute","keywords":"Enamel paint; Cementum; Artificial intelligence; Preprocessor; Computer vision; Computer science; Materials science; Dentistry; Medicine; Dentin","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001355213,0.0004372848,0.0004559515,0.001925525,0.0002028233,0.0006716951,0.0007627506,0.0009296382,0.0007295715],"category_scores_gemma":[0.00477403,0.0003601975,0.0002562714,0.00076146,0.0003249082,0.00048738,0.0004981376,0.000365552,0.0005021648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001664122,"about_ca_system_score_gemma":0.0003572493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001017877,"about_ca_topic_score_gemma":0.002397015,"domain_scores_codex":[0.9989404,0.0003140939,0.00006892539,0.0001740006,0.0004500213,0.00005257137],"domain_scores_gemma":[0.9974402,0.001028396,0.0002676647,0.0002428632,0.0009450109,0.00007578287],"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":[0.0007027553,0.0001167178,0.01193157,0.0004032903,0.00007103245,0.000304214,0.0003804659,0.004387674,0.6160111,0.000526605,0.0008502874,0.3643143],"study_design_scores_gemma":[0.00008792522,0.0008523227,0.1745934,0.0001100533,0.000231247,0.006276865,0.0004578334,0.3834877,0.4258836,0.0007049675,0.007103069,0.0002110981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4311121,0.001592086,0.5638606,0.00009629617,0.00007067183,0.0001887757,0.0001141317,0.001753525,0.001211767],"genre_scores_gemma":[0.5432067,0.0006288757,0.4548565,0.00004142757,0.00003248278,0.00008527847,0.0001168745,0.00008784515,0.0009440452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001925525,"threshold_uncertainty_score":0.007167161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01754647458584678,"score_gpt":0.2562346759918355,"score_spread":0.2386882014059887,"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."}}