{"id":"W2591443317","doi":"","title":"Automatic Corneal Nerve Fibre Detection for Diabetic Neuropathy Quantification.","year":2011,"lang":"en","type":"article","venue":"Research Explorer (The University of Manchester)","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"LMC Diabetes & Endocrinology (Canada)","funders":"","keywords":"Diabetic neuropathy; Medicine; Nerve fibre; Ophthalmology; Diabetes mellitus; Anatomy","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":[0.0006514044,0.0003541415,0.0003050277,0.001234931,0.0002215752,0.0004362373,0.0004616734,0.0007357386,0.004597853],"category_scores_gemma":[0.001336466,0.0002297366,0.0002059612,0.0005372047,0.0001725538,0.0004071248,0.0004362888,0.0002834501,0.001249099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002338848,"about_ca_system_score_gemma":0.0002719585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002496205,"about_ca_topic_score_gemma":0.006199385,"domain_scores_codex":[0.9994972,0.0001435922,0.00001924868,0.00009439638,0.0002005889,0.00004489337],"domain_scores_gemma":[0.9992894,0.0003077763,0.00006602209,0.00006288112,0.0002441657,0.00002968499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009403895,0.0001316936,0.008928083,0.0006396328,0.00009257033,0.0001171923,0.000102996,0.003510318,0.3926796,0.0008221014,0.006180172,0.5858551],"study_design_scores_gemma":[0.0002225228,0.0008783971,0.1936334,0.000255267,0.0002628792,0.002858333,0.0002287759,0.4088526,0.3699623,0.002569226,0.02005973,0.0002164697],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3294006,0.007003752,0.6448287,0.0003079415,0.0002421882,0.0001978442,0.002233587,0.005694317,0.0100909],"genre_scores_gemma":[0.6969784,0.001508439,0.2918476,0.0001589834,0.00008586235,0.0001415558,0.001079048,0.0001575715,0.008042528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004597853,"threshold_uncertainty_score":0.01538134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1283397229116804,"score_gpt":0.2915738798623408,"score_spread":0.1632341569506605,"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."}}