{"id":"W2053450714","doi":"10.1016/j.aodf.2010.03.009","title":"Cone Beam Computed Tomographic Findings in Temporomandibular Joint Disorders","year":2010,"lang":"en","type":"article","venue":"Alpha Omegan","topic":"Temporomandibular Joint Disorders","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Temporomandibular joint; Cone beam computed tomography; Magnetic resonance imaging; Medicine; Computed tomography; Computed tomographic; Radiography; Radiology; Tomography; TMJ disorders; Tomographic reconstruction; Computed tomography laser mammography; Nuclear medicine; Preclinical imaging; Orthodontics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001356253,0.0004214188,0.0006671159,0.0006215894,0.0005981557,0.00002739851,0.000454809,0.0005447929,0.0009214691],"category_scores_gemma":[0.0003089882,0.0004151228,0.0001804399,0.001092037,0.0002666045,0.0002892817,0.0002412485,0.002221939,0.0006667103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008154302,"about_ca_system_score_gemma":0.0002254591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001723122,"about_ca_topic_score_gemma":0.0129952,"domain_scores_codex":[0.9963015,0.000309465,0.001071638,0.000704212,0.000450091,0.001163037],"domain_scores_gemma":[0.9980985,0.0003730964,0.0002747954,0.0008357558,0.00009115736,0.0003266807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008336628,0.0004925881,0.9270272,0.0002339383,0.00009792935,0.00005441536,0.004584609,0.00001016418,0.01359106,0.00539128,0.04783711,0.0005963701],"study_design_scores_gemma":[0.005303248,0.0001998675,0.7800393,0.0002306918,0.00003598855,0.000009331516,0.001895178,0.0003068688,0.0003424028,0.005268505,0.2055728,0.0007958912],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829926,0.0001781113,0.0001701029,0.007700965,0.001579079,0.001607088,0.00003898252,0.0004282034,0.005304862],"genre_scores_gemma":[0.9967516,0.00005259125,0.0007220005,0.0009807403,0.0001607952,0.0001611959,0.0002570837,0.0001023224,0.0008116373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1577357,"threshold_uncertainty_score":0.9999918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01896675176057236,"score_gpt":0.3173821771952772,"score_spread":0.2984154254347048,"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."}}