{"id":"W2546164798","doi":"10.1097/iae.0000000000001354","title":"Iris Atrophy","year":2016,"lang":"en","type":"article","venue":"Retina","topic":"Ocular and Laser Science Research","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Columbia College","funders":"","keywords":"Humanities; IRIS (biosensor); Art; Philosophy; Gerontology; Medicine; Artificial intelligence; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001504068,0.00003300254,0.00006266011,0.00003366488,0.00002682845,0.000005840981,0.00005455124,0.00002271585,0.0006831115],"category_scores_gemma":[0.0001173194,0.00001637108,0.00004365015,0.0001093053,0.00006511178,0.00003232774,0.000024807,0.00003985324,0.0009262466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002362236,"about_ca_system_score_gemma":0.00004413619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001044756,"about_ca_topic_score_gemma":5.79193e-7,"domain_scores_codex":[0.9994417,0.00001453856,0.00004856697,0.0001105002,0.0002177466,0.0001669231],"domain_scores_gemma":[0.999635,0.00002416334,0.000007740081,0.0001823601,0.00003817966,0.0001125333],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001463666,0.0001018514,0.1391873,0.00005834195,0.00002287051,0.000309273,0.0001004019,5.639897e-8,0.4268201,0.001744782,0.02627561,0.4052331],"study_design_scores_gemma":[0.001804029,0.0008169763,0.2489154,0.000231066,0.00002424289,0.0001442734,0.00004345971,0.00006000243,0.08709698,0.0007777787,0.659914,0.0001718425],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9425782,0.000135829,0.0009212731,0.01301017,0.00005653549,0.000102245,0.000001316607,0.00004116722,0.04315327],"genre_scores_gemma":[0.9872111,0.00006596022,0.0004343405,0.0001188651,0.00009804265,0.000002372104,3.915194e-7,0.000004394992,0.01206453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6336384,"threshold_uncertainty_score":0.9998516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01813778204188163,"score_gpt":0.3091724202462525,"score_spread":0.2910346382043709,"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."}}