{"id":"W2945789372","doi":"10.1016/j.neucom.2019.05.039","title":"A spatial-aware joint optic disc and cup segmentation method","year":2019,"lang":"en","type":"article","venue":"Neurocomputing","topic":"Glaucoma and retinal disorders","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Postdoctoral Science Foundation of Central South University; National Natural Science Foundation of China; China Postdoctoral Science Foundation; Education Department of Hunan Province","keywords":"Artificial intelligence; Computer science; Segmentation; Pixel; Computer vision; Spatial analysis; Pattern recognition (psychology); Pyramid (geometry); Optic cup (embryology); Joint (building); Image segmentation; Probabilistic logic; Scale (ratio); Mathematics; Remote sensing; Cartography; Geology; Geography","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":[0.0001135617,0.0001019555,0.000179985,0.0000603651,0.00005663873,0.00002146627,0.0000281976,0.00003364051,0.00004121501],"category_scores_gemma":[0.00002610765,0.00008240429,0.0000473764,0.0000812217,0.00001492098,0.00003492,0.0000570237,0.000141809,0.00004398506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001256376,"about_ca_system_score_gemma":0.00001710085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005827705,"about_ca_topic_score_gemma":0.000001658758,"domain_scores_codex":[0.9992375,0.00005278982,0.0001628282,0.0002374025,0.0001450545,0.0001644703],"domain_scores_gemma":[0.999663,0.00006461672,0.00006252933,0.0001100786,0.00002843341,0.00007137578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001422722,0.0001901815,0.5306759,0.001073351,0.00006890668,0.0001543994,0.002057205,0.0001896834,0.1770371,0.0002656849,0.0002854129,0.2878599],"study_design_scores_gemma":[0.002068107,0.0005451511,0.8271376,0.0002453557,0.00009176441,0.0003864719,0.0007137739,0.1639292,0.003936395,0.00008945925,0.0006608592,0.0001958751],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787546,0.00005754044,0.01836618,0.0007853323,0.0001657454,0.0004361874,4.662021e-7,0.00005878599,0.00137518],"genre_scores_gemma":[0.9880936,0.000007050913,0.01109296,0.0005004182,0.00007004759,0.000003072707,0.000007330032,0.00001824933,0.0002072371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2964617,"threshold_uncertainty_score":0.336035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01263462546258134,"score_gpt":0.2795869890327118,"score_spread":0.2669523635701305,"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."}}