{"id":"W7160404092","doi":"10.1109/dasa68193.2025.11498909","title":"Artificial Intelligence Techniques for Dental Artifact Suppression in Medical Imaging","year":2025,"lang":"","type":"article","venue":"","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medical imaging; Artifact (error); Image processing; Computed tomography; Pattern recognition (psychology)","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":[0.01744735,0.001124984,0.002953849,0.006735282,0.0004188917,0.003023587,0.001506181,0.001551813,0.002188271],"category_scores_gemma":[0.05282521,0.0005212046,0.004424339,0.004086602,0.001351326,0.001853643,0.001256683,0.001581398,0.0002987153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001673916,"about_ca_system_score_gemma":0.004236197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001943606,"about_ca_topic_score_gemma":0.004519316,"domain_scores_codex":[0.9841455,0.008002316,0.004114665,0.0008188226,0.002780822,0.0001379872],"domain_scores_gemma":[0.9478686,0.04597341,0.00330594,0.0007650002,0.001972757,0.0001142929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002019519,0.00005738277,0.001040515,0.3599819,0.004902845,0.00008932892,0.0002198656,0.001367607,0.0007025215,0.003922053,0.002170536,0.6253436],"study_design_scores_gemma":[0.0005439383,0.001702097,0.0157616,0.6980029,0.03433074,0.001891762,0.0007505482,0.005086529,0.005690639,0.02667503,0.2092905,0.0002737486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0007867635,0.9943135,0.003473099,0.0005311771,0.0001438946,0.0001852855,0.00007819548,0.00001769879,0.0004703877],"genre_scores_gemma":[0.02891796,0.9441608,0.0245628,0.000919745,0.0002845088,0.00074526,0.0001667906,0.00001668078,0.0002254588],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01744735,"threshold_uncertainty_score":0.09227151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01620184033582823,"score_gpt":0.3448673690408977,"score_spread":0.3286655287050694,"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."}}