{"id":"W7115825496","doi":"","title":"OPTICAL PROPERTIES FOR LUNG CANCER MARGIN DETECTION","year":2023,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lung cancer; Cancer; Surgical margin; Resection; Lung; Margin (machine learning); Resection margin","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007051653,0.0003793235,0.0002041093,0.0007622311,0.0002982188,0.0004995657,0.0003219515,0.0004562996,0.002589344],"category_scores_gemma":[0.0006679921,0.0002898089,0.0002621796,0.0004328026,0.000181296,0.0005961324,0.0003401194,0.000569824,0.0008968654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004606298,"about_ca_system_score_gemma":0.0003013935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001017146,"about_ca_topic_score_gemma":0.002571909,"domain_scores_codex":[0.9996424,0.0000523586,0.00001205958,0.00007885529,0.0001882241,0.00002606698],"domain_scores_gemma":[0.9995833,0.0001319276,0.00008146394,0.000033855,0.0001442428,0.00002511017],"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":[0.00005965435,0.00002766645,0.001222698,0.0001041027,0.000006418165,0.00001796308,0.00003158655,0.0002899464,0.9761353,0.0002185366,0.0003236687,0.02156251],"study_design_scores_gemma":[0.000007900687,0.0002621353,0.01176951,0.00002493176,0.00003690147,0.0002784366,0.00009288218,0.005944789,0.9744504,0.000281837,0.006816348,0.00003388311],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7385552,0.02878333,0.2029677,0.0008183059,0.0002472403,0.0003215559,0.001260044,0.001456616,0.02559008],"genre_scores_gemma":[0.8133827,0.007803511,0.1620459,0.0002749256,0.00005357929,0.0001766703,0.000641857,0.000144154,0.01547661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002589344,"threshold_uncertainty_score":0.008662224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01838165228351023,"score_gpt":0.2774310270718516,"score_spread":0.2590493747883414,"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."}}