{"id":"W969608678","doi":"10.1007/s00216-015-8914-9","title":"Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation","year":2015,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":76,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver Coastal Health Research Institute; University of British Columbia; Vancouver Coastal Health; BC Cancer Agency","funders":"Canadian Institutes of Health Research","keywords":"Receiver operating characteristic; Cohort; Principal component analysis; Gold standard (test); Linear discriminant analysis; Confidence interval; Internal medicine; Medicine; Cohort study; Partial least squares regression; Area under the curve; Oncology; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004889036,0.0002403803,0.0003166695,0.00005361075,0.00005469786,0.00006894624,0.0002617679,0.000408712,0.0003192684],"category_scores_gemma":[0.000359871,0.000202825,0.0001125913,0.0002628947,0.0003540182,0.00001285329,0.0001489621,0.000227348,0.000005020818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001277342,"about_ca_system_score_gemma":0.0001506535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009900418,"about_ca_topic_score_gemma":0.00002134389,"domain_scores_codex":[0.9979932,0.00003856361,0.0003879121,0.0006598766,0.0004121889,0.0005082602],"domain_scores_gemma":[0.9988053,0.00005122097,0.00005598508,0.0003221781,0.0001370149,0.0006282491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002465064,0.0002501117,0.0009511553,0.00008082191,0.00005481959,0.000006736985,0.000009611916,0.000002064058,0.9951345,0.00007827685,0.001933977,0.001251422],"study_design_scores_gemma":[0.0008228128,0.0003812644,0.0001831851,0.00002660191,0.00005701098,0.00001475042,0.00004613027,0.02367051,0.9687622,0.001630246,0.004112648,0.0002927136],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922528,0.00009341798,0.001528171,0.0006764521,0.00002913085,0.0002479246,0.00003800221,0.00005462098,0.005079438],"genre_scores_gemma":[0.9941366,0.0002359898,0.001883678,0.0001271222,0.000546855,0.0001144364,0.0001080223,0.00003024967,0.002817001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02637237,"threshold_uncertainty_score":0.8270962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01809207438083682,"score_gpt":0.3445596546691541,"score_spread":0.3264675802883173,"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."}}