{"id":"W1504050639","doi":"10.1111/cid.12221","title":"Linear Measurement Accuracy of Eight Cone Beam Computed Tomography Scanners","year":2014,"lang":"en","type":"article","venue":"Clinical Implant Dentistry and Related Research","topic":"Dental Radiography and Imaging","field":"Dentistry","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cone beam computed tomography; Calipers; Intraclass correlation; Scanner; Imaging phantom; Nuclear medicine; Medicine; Gold standard (test); DICOM; Standard deviation; Mathematics; Reproducibility; Computed tomography; Computer science; Artificial intelligence; Radiology; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.007784608,0.0007305939,0.0005450805,0.002096903,0.0002479068,0.001293114,0.001128008,0.0007454491,0.001324446],"category_scores_gemma":[0.02758244,0.0007021002,0.0005191754,0.0009851702,0.0007070926,0.0008360799,0.001268106,0.0004944802,0.0005482025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000573773,"about_ca_system_score_gemma":0.0006122969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009434647,"about_ca_topic_score_gemma":0.001575799,"domain_scores_codex":[0.9902858,0.002492847,0.001249505,0.001792719,0.003961413,0.0002177894],"domain_scores_gemma":[0.9718327,0.01608198,0.00340852,0.002588495,0.005663251,0.0004250573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002444907,0.0001497651,0.6312647,0.0007017778,0.0005382986,0.0003442602,0.0009468888,0.005535398,0.08510611,0.0003707866,0.0006726185,0.2719245],"study_design_scores_gemma":[0.0002282522,0.002117762,0.793452,0.0006199969,0.001222924,0.009245123,0.0006731855,0.05902358,0.1276105,0.0008664356,0.004691923,0.0002484002],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9410311,0.003555168,0.05070769,0.0001349521,0.00007327386,0.0001528242,0.0004592116,0.001029765,0.002855988],"genre_scores_gemma":[0.9584001,0.0004953104,0.04022005,0.00004713072,0.00001336029,0.00005550317,0.0003231221,0.00008579668,0.0003595923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007784608,"threshold_uncertainty_score":0.0411694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1078274032965277,"score_gpt":0.413929920680141,"score_spread":0.3061025173836133,"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."}}