{"id":"W2335346100","doi":"10.1097/01.prs.0000463414.88094.80","title":"Abstract P94","year":2015,"lang":"en","type":"article","venue":"Plastic & Reconstructive Surgery","topic":"Digital Imaging in Medicine","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Medicine; Reconstructive surgery; Plastic surgery; Surgery; General 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":[0.0004378905,0.0002137271,0.0005355945,0.0003009135,0.00003037283,0.00003188353,0.0000645191,0.000075903,0.0003449181],"category_scores_gemma":[0.008210694,0.000182586,0.0001333177,0.0002741258,0.0004054566,0.0002684975,0.00003502148,0.0002874707,0.000661474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001448087,"about_ca_system_score_gemma":0.0005478825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002097205,"about_ca_topic_score_gemma":0.000001455818,"domain_scores_codex":[0.9984031,0.00002226848,0.0004132296,0.0003358726,0.0004455383,0.0003800468],"domain_scores_gemma":[0.9965043,0.002248102,0.0001349627,0.0002807002,0.0003036434,0.0005282892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005564257,0.0002447799,0.7833413,0.0001773031,0.000275908,0.001049812,0.0002223883,0.000008559857,0.0008762677,0.0002652843,0.06305311,0.1499288],"study_design_scores_gemma":[0.003457475,0.0002840262,0.9515954,0.001750505,0.0003318163,0.006670124,0.002055441,0.0003577222,0.003599581,0.003796367,0.02519837,0.0009031408],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.89152,0.0002193523,0.000344284,0.0003175125,0.003383043,0.0001556907,0.00001612603,0.0001867517,0.1038573],"genre_scores_gemma":[0.9974423,0.000009392416,0.001236106,0.0002785204,0.0004822541,0.0000129829,0.00003500545,0.00003655707,0.0004668692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1682541,"threshold_uncertainty_score":0.9829562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0465118383100355,"score_gpt":0.2783360774712437,"score_spread":0.2318242391612082,"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."}}