{"id":"W4392499405","doi":"10.1007/s00417-024-06432-x","title":"Comparing code-free and bespoke deep learning approaches in ophthalmology","year":2024,"lang":"en","type":"review","venue":"Graefe s Archive for Clinical and Experimental Ophthalmology","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute for Health and Care Research","keywords":"Bespoke; Code (set theory); Computer science; Artificial intelligence; Programming language; Business","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008607919,0.0006053604,0.003644469,0.0004405211,0.0001329057,0.0000489751,0.0002530137,0.0004386614,0.00003734199],"category_scores_gemma":[0.0003518991,0.0004554452,0.0009181312,0.0002038841,0.001100111,0.0000422255,0.0005875259,0.001429337,0.00002172234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003694146,"about_ca_system_score_gemma":0.00006856339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007087106,"about_ca_topic_score_gemma":0.000002487186,"domain_scores_codex":[0.9960602,0.0005827023,0.001386566,0.001270851,0.0001358132,0.0005639013],"domain_scores_gemma":[0.9978714,0.001141545,0.0002670482,0.000378096,0.00001838946,0.0003235481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003461205,0.004221963,0.2016771,0.06956761,0.007008399,0.01702694,0.002298395,0.00001247271,0.00002977308,0.005339373,0.00109608,0.6882607],"study_design_scores_gemma":[0.01241592,0.01510993,0.006407944,0.02655862,0.01433694,0.1689981,0.0031831,0.01018337,0.0000177036,0.0120421,0.7270554,0.003690818],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03702774,0.9589717,0.00001931912,0.0001261225,0.0002647979,0.0008119607,0.00005124344,0.00003778581,0.002689335],"genre_scores_gemma":[0.07483871,0.9202198,0.002312379,0.00003590852,0.0003719666,0.0003815298,0.0006003481,0.0001162044,0.001123161],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7259594,"threshold_uncertainty_score":0.9997897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3076497175863587,"score_gpt":0.4784836130208899,"score_spread":0.1708338954345312,"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."}}