{"id":"W2980788621","doi":"10.1039/c9an01144g","title":"Feature engineering applied to intraoperative<i>in vivo</i>Raman spectroscopy sheds light on molecular processes in brain cancer: a retrospective study of 65 patients","year":2019,"lang":"en","type":"article","venue":"The Analyst","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital; GDI Integrated Facility Services (Canada); Polytechnique Montréal; McGill University; Centre Hospitalier de l’Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Interpretability; Raman spectroscopy; In vivo; Feature (linguistics); Cancer; Chemistry; Nuclear magnetic resonance; Medicine; Computer science; Internal medicine; Biology; Optics; Artificial intelligence; Physics; Genetics; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053324,0.0003271941,0.0003890278,0.0012411,0.0004477218,0.0005696947,0.0002725075,0.0003718327,0.0005744745],"category_scores_gemma":[0.001516558,0.0003271761,0.00047622,0.0009327942,0.0004728621,0.0003262053,0.0004491514,0.0003121596,0.0002856418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003445006,"about_ca_system_score_gemma":0.0003258767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002990358,"about_ca_topic_score_gemma":0.002549722,"domain_scores_codex":[0.999445,0.00007017844,0.00006689318,0.0002215928,0.0001155157,0.00008084309],"domain_scores_gemma":[0.9989145,0.000230495,0.0004378334,0.0001743683,0.0001357333,0.0001070408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001816777,0.00006740121,0.9895941,0.00001886265,0.00006914471,0.0007407233,0.0002674428,0.0001839099,0.002630266,0.00002826945,0.0001594688,0.006058732],"study_design_scores_gemma":[0.000008255237,0.00036095,0.9915166,0.000008511578,0.00009603747,0.004254468,0.0005134696,0.0009001334,0.001515468,0.00006018005,0.0007475863,0.00001830999],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999319,0.000106015,0.0002903432,0.00001016551,0.000001853139,0.000005826976,0.0001660452,0.000004738712,0.00009606011],"genre_scores_gemma":[0.9994346,0.00007357528,0.0001148093,0.000006714171,0.000003390707,0.000004304928,0.0003027965,0.000003595798,0.00005617987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002990358,"threshold_uncertainty_score":0.005945921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003031177324837868,"score_gpt":0.274802103528819,"score_spread":0.2717709262039811,"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."}}