{"id":"W4281289982","doi":"10.1177/22925503221101954","title":"A Computed Tomography Scan Near Miss of an Intraorbital Wooden Foreign Body","year":2022,"lang":"en","type":"article","venue":"Plastic Surgery","topic":"Traumatic Ocular and Foreign Body Injuries","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computed tomography; Foreign body; Foreign Bodies; Medicine; Orbit (dynamics); Gold standard (test); Radiology; Tomography; Clinical history; Surgery; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003620839,0.0001753756,0.0005452274,0.0003153374,0.0001870797,0.00002420756,0.0001169681,0.00004819973,0.0007306802],"category_scores_gemma":[0.0003873602,0.0001670137,0.0002748058,0.0005277251,0.0002151506,0.00008638427,0.00007257038,0.0002164505,0.000007414202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003694317,"about_ca_system_score_gemma":0.0002088055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005625972,"about_ca_topic_score_gemma":0.000002321919,"domain_scores_codex":[0.9983549,0.00008860641,0.0004600413,0.000255159,0.000525119,0.0003161601],"domain_scores_gemma":[0.9975352,0.001729288,0.0001376428,0.0003273804,0.00006840006,0.0002020786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00422329,0.004579201,0.9340387,0.001461131,0.002016518,0.001652317,0.003203038,0.00105144,0.004669873,0.01035056,0.01662245,0.01613148],"study_design_scores_gemma":[0.003457786,0.002715165,0.9287317,0.0004336252,0.0009358969,0.00141765,0.004282135,0.04383229,0.006733248,0.002658283,0.003763756,0.001038513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965152,0.0001915941,0.0005321395,0.00003147967,0.0007219355,0.0001789745,0.0001089506,0.0001135807,0.001606112],"genre_scores_gemma":[0.9985897,0.000001368745,0.0008922311,0.0000541418,0.0001124939,0.00003362818,0.0002693201,0.00003308695,0.00001406219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04278085,"threshold_uncertainty_score":0.8000436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01504798908440425,"score_gpt":0.2361742198064538,"score_spread":0.2211262307220496,"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."}}