{"id":"W2298791748","doi":"10.1117/12.2218467","title":"Development and clinical translation of OTIS: a wide-field OCT imaging device for ex-vivo tissue characterization","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"","keywords":"Ex vivo; Characterization (materials science); Translation (biology); Optical imaging; Computer science; Biomedical engineering; Materials science; In vivo; Optics; Engineering; Nanotechnology; Chemistry; Biology; Physics","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":[0.004245738,0.000669466,0.0004367226,0.0005517033,0.0002711205,0.001172731,0.001032761,0.0007176114,0.001312576],"category_scores_gemma":[0.003764144,0.0003448303,0.0002931556,0.0002005941,0.001065943,0.0008987427,0.0006009942,0.001138371,0.0004877974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004402104,"about_ca_system_score_gemma":0.001142396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006045474,"about_ca_topic_score_gemma":0.001018719,"domain_scores_codex":[0.9987007,0.0003347744,0.00009109243,0.0001928327,0.000590901,0.00008969317],"domain_scores_gemma":[0.9974584,0.001131884,0.0003345991,0.0003006008,0.000566043,0.000208572],"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":[0.0003764791,0.0002352922,0.004215331,0.0002988144,0.00005341673,0.0003537057,0.0003690858,0.001805376,0.9093481,0.001655476,0.001393134,0.0798958],"study_design_scores_gemma":[0.0001199205,0.003752021,0.01275324,0.00009814319,0.0001067483,0.003087058,0.000217587,0.01101026,0.9452789,0.0005656391,0.02293239,0.00007819472],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4922842,0.005071113,0.4889124,0.00171166,0.0004133451,0.002006903,0.001161675,0.001964969,0.006473708],"genre_scores_gemma":[0.4951589,0.001939017,0.498162,0.0007508185,0.00009077451,0.0008003137,0.0006572311,0.0002750434,0.002165814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004245738,"threshold_uncertainty_score":0.0224539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01709077958537988,"score_gpt":0.2582508687261696,"score_spread":0.2411600891407898,"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."}}