{"id":"W1994946868","doi":"10.1097/sap.0b013e3181743386","title":"Biometric Morphing","year":2009,"lang":"en","type":"article","venue":"Annals of Plastic Surgery","topic":"Morphological variations and asymmetry","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"","keywords":"Morphing; Biometrics; Medicine; Population; Deformity; Rendering (computer graphics); Artificial intelligence; Biometric data; Computer vision; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001405074,0.0003965053,0.0003826851,0.001842013,0.0004096346,0.0009046859,0.0004101183,0.0003467982,0.009439147],"category_scores_gemma":[0.005454029,0.000220905,0.0004261307,0.001436209,0.0007224139,0.001229799,0.000848692,0.0004750865,0.001645012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003568505,"about_ca_system_score_gemma":0.0003075196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006112121,"about_ca_topic_score_gemma":0.0006136011,"domain_scores_codex":[0.9991723,0.0001657295,0.00009706656,0.0001837997,0.0003406137,0.00004039177],"domain_scores_gemma":[0.997762,0.0005174422,0.0002226105,0.0008939854,0.0005617248,0.00004216425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003474651,0.00004122051,0.009066923,0.0002186296,0.00003232644,0.0002525824,0.0004283246,0.004891539,0.09097238,0.01335633,0.00505819,0.875334],"study_design_scores_gemma":[0.00006365755,0.0009941377,0.2017307,0.0003328439,0.0002670633,0.01353178,0.001627474,0.1814252,0.3015612,0.0394155,0.2585746,0.000475897],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08606226,0.0004751554,0.8808398,0.0003480043,0.0002762782,0.0005550352,0.001591889,0.004497623,0.02535395],"genre_scores_gemma":[0.493258,0.0007289245,0.4938008,0.0002455649,0.0001009875,0.0004728519,0.001397912,0.0009517209,0.009043267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009439147,"threshold_uncertainty_score":0.03157705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2011151324527625,"score_gpt":0.3577362957569595,"score_spread":0.1566211633041971,"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."}}