{"id":"W4386973695","doi":"10.2139/ssrn.4578568","title":"ChatFFA: Interactive Visual Question Answering on Fundus Fluorescein Angiography Image Using ChatGPT","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Question answering; Fundus (uterus); Fluorescein angiography; Fluorescein; Computer science; Computer vision; Artificial intelligence; Ophthalmology; Medicine; Optics; Fluorescence; Physics; Visual acuity","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":[0.0010043,0.002956228,0.001571077,0.002398524,0.0005648241,0.001638116,0.001944726,0.002621604,0.1572655],"category_scores_gemma":[0.005206011,0.0005740788,0.001366067,0.0007442219,0.000346264,0.001466038,0.003179887,0.0009187677,0.03347887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000600484,"about_ca_system_score_gemma":0.0004514345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00386227,"about_ca_topic_score_gemma":0.004868877,"domain_scores_codex":[0.999359,0.000189641,0.00004274283,0.000149678,0.0001464884,0.0001124767],"domain_scores_gemma":[0.9967602,0.002274015,0.00006786456,0.0002677898,0.0003236186,0.0003064755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004958224,0.0005003346,0.003278669,0.002311707,0.0002724725,0.00271955,0.001232534,0.005429074,0.02892475,0.002343607,0.5172147,0.4308145],"study_design_scores_gemma":[0.002534805,0.001323297,0.02273379,0.001399667,0.0003812443,0.004114204,0.001901581,0.4454859,0.102383,0.03454819,0.3824714,0.0007228228],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.02873107,0.0009165748,0.2357232,0.0008540338,0.0008402962,0.001349215,0.0376858,0.6754473,0.01845246],"genre_scores_gemma":[0.3615951,0.001016991,0.4229084,0.001991929,0.001025151,0.005365942,0.08441588,0.05434822,0.06733233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1572655,"threshold_uncertainty_score":0.5261055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01956091936299083,"score_gpt":0.3460277235011991,"score_spread":0.3264668041382083,"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."}}