{"id":"W2295085248","doi":"10.1117/1.jbo.21.1.016007","title":"Intraoperative imaging of pediatric vocal fold lesions using optical coherence tomography","year":2016,"lang":"en","type":"article","venue":"Journal of Biomedical Optics","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Optical coherence tomography; Laryngoscopy; Medicine; Larynx; Biomedical engineering; Lesion; Tomography; Medical imaging; In vivo; Preclinical imaging; Radiology; Pathology; Anatomy; Surgery; Intubation","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":[0.0003800371,0.0001975946,0.0004023531,0.0005058854,0.00005331809,0.00002660199,0.0004007524,0.0001423124,0.00009325263],"category_scores_gemma":[0.0002988684,0.0001319727,0.000243577,0.001066432,0.0005425353,0.0002570725,0.00005938802,0.0003697776,0.000008233911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006528653,"about_ca_system_score_gemma":0.0001324559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001311541,"about_ca_topic_score_gemma":5.012158e-7,"domain_scores_codex":[0.9978929,0.00003690291,0.0009479076,0.0001442631,0.000617456,0.0003606004],"domain_scores_gemma":[0.9981553,0.0006000599,0.00020036,0.0002177927,0.0003674121,0.000459101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001755146,0.002190852,0.04263215,0.0004731637,0.001075541,0.0003552952,0.0007160485,0.003127935,0.7455531,0.02297449,0.004044251,0.1766817],"study_design_scores_gemma":[0.02212665,0.007574389,0.1024748,0.004915565,0.006714072,0.002578913,0.00324631,0.4844456,0.3121559,0.03982403,0.006558561,0.007385182],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5208868,0.0006082117,0.4767591,0.0005384679,0.0004455803,0.0001529076,0.00003573613,0.00005823511,0.0005149583],"genre_scores_gemma":[0.9394804,0.000278467,0.05978687,0.00002078567,0.0004004359,0.000003444784,8.116131e-7,0.00002528519,0.000003560158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4813177,"threshold_uncertainty_score":0.538169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631075785358956,"score_gpt":0.2610332879194136,"score_spread":0.244722530065824,"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."}}