{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00613802,0.0002439123,0.00061311,0.0004772024,0.000415734,0.0001311478,0.0005689506,0.0004442244,0.0001648325],"category_scores_gemma":[0.001524764,0.0002121822,0.000429283,0.00118663,0.001454664,0.0002200489,0.0003298804,0.001646227,0.000275866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002082519,"about_ca_system_score_gemma":0.0000730118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007939962,"about_ca_topic_score_gemma":0.00001374734,"domain_scores_codex":[0.9948598,0.001046394,0.001329644,0.0007072204,0.001339224,0.0007177214],"domain_scores_gemma":[0.9961367,0.001882037,0.0002976704,0.0005931155,0.0005922834,0.0004982571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003444382,0.007007263,0.4934535,0.003307011,0.007966977,0.02740833,0.0005728148,0.00009543961,0.06907768,0.006184175,0.2254065,0.156076],"study_design_scores_gemma":[0.01338836,0.001938805,0.8564625,0.002412434,0.0005341287,0.03940544,0.0007870873,0.006875884,0.02438059,0.005518381,0.04677605,0.001520282],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884356,0.002068819,0.0003341682,0.0001731879,0.005844454,0.0003989038,0.00009510424,0.0000850068,0.002564793],"genre_scores_gemma":[0.9983715,0.0004389502,0.0001930093,0.00005367653,0.0002139674,0.000009373975,0.00009118786,0.00002917106,0.000599205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3630091,"threshold_uncertainty_score":0.865254,"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."}}