{"id":"W4393390090","doi":"10.54364/aaiml.2024.41115","title":"Application of Machine Learning in Orthodontics: A Bibliometric Analysis","year":2024,"lang":"en","type":"article","venue":"Advances in Artificial Intelligence and Machine Learning","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre; Children's Aid Society; Holland Bloorview Kids Rehabilitation Hospital","funders":"","keywords":"Orthodontics; Computer science; Medicine","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.02482279,0.0008752475,0.003448115,0.2023817,0.001496458,0.006361213,0.001422969,0.001158971,0.004988012],"category_scores_gemma":[0.09106679,0.000520484,0.005035379,0.2108548,0.001314872,0.004958625,0.002856537,0.0008228171,0.0008088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004337666,"about_ca_system_score_gemma":0.006360231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003829265,"about_ca_topic_score_gemma":0.005383528,"domain_scores_codex":[0.9677811,0.007725085,0.008370304,0.001687147,0.01384585,0.0005904631],"domain_scores_gemma":[0.8828346,0.08675008,0.01494236,0.002572868,0.0119351,0.000964951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004331942,0.0002706313,0.4250805,0.1065355,0.01137108,0.0009813566,0.00317483,0.003222822,0.000829915,0.006791354,0.01890951,0.4223994],"study_design_scores_gemma":[0.0002750362,0.0008686135,0.7347554,0.05549496,0.03066732,0.004661436,0.009778772,0.01767777,0.002440784,0.01553183,0.1274305,0.000417564],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3215014,0.5655364,0.01289653,0.01018333,0.0009183944,0.003871293,0.0431297,0.0004729374,0.04148999],"genre_scores_gemma":[0.7921691,0.1738223,0.01767819,0.0004953855,0.001043596,0.002235251,0.0111552,0.00007885705,0.001322138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7976183,"threshold_uncertainty_score":0.131277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0251438292327605,"score_gpt":0.3436803518118739,"score_spread":0.3185365225791134,"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."}}