{"id":"W4408565821","doi":"10.1109/icecer62944.2024.10920356","title":"Exploring ResNet50 with Advanced Learning Strategies for Improved Ocular Disease Diagnosis","year":2024,"lang":"en","type":"article","venue":"","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Computer science; Disease; Artificial intelligence; Medicine; Pathology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002739941,0.002015024,0.0008222003,0.001026162,0.0002915073,0.001122646,0.001533619,0.001457849,0.002055738],"category_scores_gemma":[0.004956555,0.0003883264,0.0009341135,0.0004872708,0.0004189429,0.001547885,0.0008647998,0.001605645,0.00122547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001256473,"about_ca_system_score_gemma":0.001275202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009423506,"about_ca_topic_score_gemma":0.01053819,"domain_scores_codex":[0.9994642,0.0002001183,0.00003492558,0.0001447163,0.00008168481,0.00007432211],"domain_scores_gemma":[0.9989844,0.0005082098,0.00008475131,0.0001206173,0.0002360149,0.00006594846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008691384,0.0007853221,0.008735565,0.0002761758,0.0003199349,0.0003151728,0.0001530842,0.6068992,0.01225175,0.003835305,0.01119259,0.3543668],"study_design_scores_gemma":[0.00002241762,0.0001793241,0.0005755628,0.00003351521,0.00003884175,0.00004376881,0.00002443663,0.9901597,0.004796673,0.002790614,0.001320415,0.00001473308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4677462,0.008481959,0.4861195,0.00557196,0.0008779534,0.000479892,0.001554189,0.01175539,0.01741287],"genre_scores_gemma":[0.8855496,0.0008148461,0.1056431,0.001017148,0.0001278519,0.0001882017,0.001395571,0.0002365213,0.005027123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009423506,"threshold_uncertainty_score":0.01873732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04472183678271845,"score_gpt":0.2613006030229609,"score_spread":0.2165787662402425,"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."}}