{"id":"W4311627575","doi":"10.3390/healthcare10122454","title":"Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review","year":2022,"lang":"en","type":"review","venue":"Healthcare","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Khalid University","keywords":"Scopus; Cephalometric analysis; Artificial intelligence; Identification (biology); Computer science; Systematic review; Inclusion and exclusion criteria; MEDLINE; Landmark; Machine learning; Medical physics; Medicine; Orthodontics; Alternative medicine; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001161123,0.0002327087,0.001400736,0.0007871602,0.0001267574,0.00003724466,0.0002358516,0.00008919529,0.0000242501],"category_scores_gemma":[0.0002026715,0.0002165362,0.0001008476,0.002269443,0.00004433902,0.0001204258,0.0001041642,0.0003092234,0.00001872355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001269658,"about_ca_system_score_gemma":0.0001098388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000563421,"about_ca_topic_score_gemma":0.00007423114,"domain_scores_codex":[0.9970715,0.0003115946,0.001685625,0.0004361646,0.0003026611,0.0001924541],"domain_scores_gemma":[0.9983601,0.000254456,0.0009016513,0.0003593779,0.00004891029,0.00007552715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[9.006608e-7,0.00001758705,0.001500302,0.5431712,0.00001495314,0.000002386638,0.0000601038,8.375167e-9,1.623214e-8,0.00006673241,0.000006427236,0.4551594],"study_design_scores_gemma":[0.00005562476,0.00004916323,0.00413555,0.8897472,0.0007980373,0.0003830669,0.0004189798,0.00005181668,0.000002452531,0.00005613813,0.103737,0.0005649941],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004018243,0.996874,0.00005102528,0.00001229401,0.0001200708,0.002465004,0.00004144523,0.00001950639,0.00001486756],"genre_scores_gemma":[0.003460417,0.993232,0.0001064222,0.0000415524,0.000015187,0.002947115,0.0001592076,0.00002382891,0.00001432573],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4545944,"threshold_uncertainty_score":0.8830088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06705411543511013,"score_gpt":0.3652771897682628,"score_spread":0.2982230743331527,"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."}}