{"id":"W2342531805","doi":"10.1117/12.2209686","title":"In vivo imaging of pulmonary nodule and vasculature using endoscopic co-registered optical coherence tomography and autofluorescence imaging (Conference Presentation)","year":2016,"lang":"en","type":"article","venue":"","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Autofluorescence; Optical coherence tomography; Medicine; Pathology; Radiology; Preclinical imaging; Lung; Elastin; Endomicroscopy; In vivo; Airway; Confocal; Biology; Internal medicine","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":[0.0004403751,0.0001996688,0.000161238,0.0004516375,0.0001557474,0.0002198754,0.0001191204,0.0004528085,0.001797441],"category_scores_gemma":[0.0006839083,0.000191149,0.0001474585,0.0001448557,0.0002533172,0.0003864355,0.0002218509,0.0003078041,0.0003096071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009888777,"about_ca_system_score_gemma":0.0001056817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004265688,"about_ca_topic_score_gemma":0.0006115717,"domain_scores_codex":[0.9998389,0.00005035883,0.00001101359,0.00003617883,0.00003344543,0.00003000878],"domain_scores_gemma":[0.9997023,0.0001179868,0.00004403182,0.00004548173,0.00004848806,0.00004173662],"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":[0.0008204005,0.0001363392,0.02326869,0.00007959728,0.00003188967,0.002010406,0.0001346575,0.0003728795,0.9438559,0.0001005146,0.0001756309,0.02901327],"study_design_scores_gemma":[0.00009974595,0.00370052,0.3476917,0.00002681203,0.0001805453,0.05476143,0.000333976,0.01291976,0.5765218,0.000265244,0.003432357,0.00006623293],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883415,0.000810901,0.009499336,0.00005492539,0.00000779476,0.00002629262,0.00005901644,0.00006202638,0.001138313],"genre_scores_gemma":[0.9841033,0.0003888198,0.01468012,0.00005584426,0.00001598459,0.00002478856,0.00009638253,0.00001885135,0.0006159523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001797441,"threshold_uncertainty_score":0.006013036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01534033925383064,"score_gpt":0.2594347410141797,"score_spread":0.2440944017603491,"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."}}