{"id":"W226305295","doi":"10.1097/01.prs.0000445029.96516.5b","title":"Abstract 16","year":2014,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery","topic":"Digital Imaging in Medicine","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"","keywords":"Medicine; Reconstructive surgery; Plastic surgery; General surgery; Surgery","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":[0.0004204996,0.0002150767,0.0005524826,0.0002875081,0.00004983972,0.00003006884,0.0000635856,0.00007460193,0.0008566998],"category_scores_gemma":[0.007645584,0.0001828504,0.0001617493,0.0002159435,0.0003998658,0.0001928661,0.00002825719,0.0002834713,0.0005345114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000105957,"about_ca_system_score_gemma":0.0001483673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001524165,"about_ca_topic_score_gemma":0.000002153141,"domain_scores_codex":[0.9984922,0.00002898175,0.0004098913,0.0003563218,0.0003303693,0.0003821701],"domain_scores_gemma":[0.9943036,0.004811738,0.0001422309,0.0003063288,0.0001583025,0.0002777325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002471088,0.0001617106,0.5414326,0.0002692091,0.0002007008,0.0001233678,0.00005034565,0.00000313533,0.001763707,0.0008235043,0.01931246,0.4356121],"study_design_scores_gemma":[0.001439804,0.0001485206,0.9613169,0.001397546,0.0001980958,0.002000764,0.0002550188,0.0003236789,0.003666946,0.003091272,0.02560866,0.0005527788],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8392993,0.0000778086,0.00207537,0.0002582532,0.002524026,0.0001323588,0.00000965475,0.0001835011,0.1554397],"genre_scores_gemma":[0.9977036,0.000009653151,0.0008119662,0.0004149234,0.0005497293,0.00001189896,0.00003226242,0.00003681723,0.0004291298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4350594,"threshold_uncertainty_score":0.9380262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01822936160301568,"score_gpt":0.2499230117494317,"score_spread":0.231693650146416,"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."}}