{"id":"W4254433509","doi":"10.1109/cbms.2004.1311771","title":"RetsoftPlus: a tool for retinal image analysis","year":2004,"lang":"en","type":"article","venue":"","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Retinal; Image (mathematics); Computer vision; Artificial intelligence; Ophthalmology; Medicine","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":[0.001346174,0.001551971,0.000920932,0.003162458,0.0004141193,0.001568983,0.002157174,0.001228374,0.05281705],"category_scores_gemma":[0.005046171,0.001070492,0.001199098,0.0012591,0.0003899929,0.001589133,0.002410259,0.001137185,0.02678855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003187876,"about_ca_system_score_gemma":0.0007719689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001291393,"about_ca_topic_score_gemma":0.001682488,"domain_scores_codex":[0.9987638,0.0001484326,0.000155996,0.0002160482,0.0006431297,0.00007256804],"domain_scores_gemma":[0.9976732,0.001225032,0.0001569767,0.0003493044,0.0004619727,0.0001334978],"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":[0.0006327179,0.0001534913,0.001283097,0.001185897,0.0001731598,0.0008009571,0.0003332355,0.002390639,0.05084693,0.003531078,0.1410369,0.7976319],"study_design_scores_gemma":[0.0005741521,0.00058103,0.01104337,0.0006480326,0.0002909741,0.009819172,0.0002109992,0.08803226,0.1495981,0.01588027,0.7225588,0.0007627294],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00391944,0.001113557,0.6389101,0.0001556359,0.0002382527,0.0004215557,0.003446593,0.3441546,0.007640329],"genre_scores_gemma":[0.05997312,0.001552886,0.8261293,0.0007573576,0.0002656274,0.001646859,0.01228679,0.05536955,0.04201854],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05281705,"threshold_uncertainty_score":0.1766906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01073832788215695,"score_gpt":0.306939117045048,"score_spread":0.2962007891628911,"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."}}