{"id":"W2317664031","doi":"10.1002/j.1538-9235.2002.tb04263.x","title":"USE OF THE ARTIFICIAL IRIS IN PATIENTS WITH ANIRIDIA.","year":2002,"lang":"en","type":"article","venue":"Optometry and Vision Science","topic":"Intraocular Surgery and Lenses","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Aniridia; IRIS (biosensor); Ophthalmology; Medicine; Optometry; Computer science; Artificial intelligence; Biology","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":[0.000242131,0.0002029303,0.000266075,0.0004294673,0.0006377152,0.0003955674,0.0001639819,0.0006126802,0.001564088],"category_scores_gemma":[0.00233207,0.00009782019,0.0003420123,0.000313557,0.0003259811,0.0003836413,0.0002328302,0.0007165301,0.0001894708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002125393,"about_ca_system_score_gemma":0.0003854307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008743231,"about_ca_topic_score_gemma":0.001031885,"domain_scores_codex":[0.999761,0.00006212263,0.0000288488,0.0000205497,0.00006541265,0.00006204721],"domain_scores_gemma":[0.9993267,0.0002459277,0.0001762535,0.0000453383,0.00003335133,0.000172369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004060339,0.000723775,0.827852,0.0003181362,0.0001947892,0.05181976,0.0009447529,0.0004960796,0.007016001,0.001158603,0.003146204,0.1022696],"study_design_scores_gemma":[0.0001748331,0.004288135,0.7201182,0.0002949357,0.0002199582,0.2616238,0.001774922,0.001105891,0.002084523,0.001276792,0.006967972,0.00007015961],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762354,0.007911628,0.0004004595,0.0009385672,0.0001201427,0.00002468464,0.0001091146,0.00002757045,0.01423246],"genre_scores_gemma":[0.9977747,0.001449182,0.0001462079,0.0001519735,0.00005433945,0.00000827111,0.00004448854,0.000002717996,0.0003680753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001564088,"threshold_uncertainty_score":0.005232394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02758382896732308,"score_gpt":0.3507492305968874,"score_spread":0.3231654016295643,"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."}}