{"id":"W2041612765","doi":"10.1117/1.2362722","title":"Classification of burn injuries using near-infrared spectroscopy","year":2006,"lang":"en","type":"article","venue":"Journal of Biomedical Optics","topic":"Forensic Entomology and Diptera Studies","field":"Agricultural and Biological Sciences","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; National Research Council Canada; National Research Council Institute for Biodiagnostics","funders":"","keywords":"Partial least squares regression; Burn wound; Medicine; Surgery; Computer science; Machine learning; Wound healing","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":[0.0002411601,0.00007341497,0.0002203437,0.00002033518,0.00009187265,0.0000187698,0.0001263683,0.00009816301,0.00007956388],"category_scores_gemma":[0.00009381571,0.00002681603,0.00009653767,0.0002284956,0.0004770857,0.00007318729,0.00003018364,0.000123414,0.000002111353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002032702,"about_ca_system_score_gemma":0.00002186891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002773858,"about_ca_topic_score_gemma":0.00001066662,"domain_scores_codex":[0.9990306,0.00003364176,0.0004570517,0.00006748143,0.0002736289,0.0001376353],"domain_scores_gemma":[0.9992535,0.0001238081,0.0003713906,0.00002717643,0.0001661086,0.00005808796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001846193,0.0005026425,0.03553353,0.00002269348,0.00008396456,0.00003370819,0.0001346703,0.000008676983,0.9438618,0.002925543,0.008381441,0.008326755],"study_design_scores_gemma":[0.001027347,0.00340662,0.891389,0.0002172622,0.0002127705,0.0002319384,0.001096907,0.003284574,0.04663333,0.02875087,0.02336073,0.0003886093],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970902,0.0003147396,0.0001710264,0.001192075,0.0002758577,0.00002933106,0.00000897131,0.000005861513,0.0009119771],"genre_scores_gemma":[0.9907292,0.00004388934,0.00868811,0.0000525565,0.0004287446,2.062154e-7,0.00000703772,5.065805e-7,0.00004980904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8972284,"threshold_uncertainty_score":0.1757842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099872776675434,"score_gpt":0.265831539782583,"score_spread":0.2448328120158287,"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."}}