{"id":"W1987178767","doi":"10.1111/j.1365-2273.2004.00902.x","title":"3-D optical coherence tomography of the laryngeal mucosa*","year":2004,"lang":"en","type":"article","venue":"Clinical Otolaryngology","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nanoacademic Technologies","funders":"University of Kent; New York Eye and Ear Infirmary of Mount Sinai","keywords":"Optical coherence tomography; Tomography; Medicine; Physics; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003311926,0.0001868567,0.0004129379,0.0000761983,0.00006512405,0.00001124412,0.0007352589,0.0003377114,0.00009099617],"category_scores_gemma":[0.0002290084,0.0001425256,0.0004118467,0.0007779436,0.001100866,0.000076365,0.0001293968,0.0007011702,0.00009470096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001917417,"about_ca_system_score_gemma":0.00006162099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001081074,"about_ca_topic_score_gemma":0.00004289191,"domain_scores_codex":[0.9982833,0.00007888125,0.0007742324,0.0003020698,0.000186665,0.0003748673],"domain_scores_gemma":[0.9984074,0.0004803104,0.00007791738,0.0007671561,0.00008351215,0.0001837114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008584472,0.001510428,0.5997649,0.0002193114,0.0005227051,0.00003500757,0.0002102149,0.004668621,0.01403998,0.3651445,0.001741702,0.01205675],"study_design_scores_gemma":[0.001142071,0.0003182359,0.9683897,0.00005200868,0.00009212334,0.00003025022,0.00002008923,0.0004829872,0.0057843,0.02024583,0.003117121,0.0003253122],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816594,0.0002441421,0.003732081,0.0006596555,0.0005743837,0.0004704165,0.00001875988,0.000255079,0.01238608],"genre_scores_gemma":[0.9943905,0.00004260374,0.005090912,0.0002575263,0.00009548018,0.00008224635,0.000004315971,0.00002544165,0.00001100515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3686247,"threshold_uncertainty_score":0.5812026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02143120620645442,"score_gpt":0.284171616240955,"score_spread":0.2627404100345005,"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."}}