{"id":"W3096863168","doi":"10.1167/jov.20.11.255","title":"Learning from few examples: Classifying sex from retinal images","year":2020,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Fundus (uterus); Machine learning; Deep learning; Usability; Artificial neural network; Pipeline (software); Pattern recognition (psychology); 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":[0.001361442,0.0006966989,0.0005080606,0.001099436,0.0002774116,0.0006681822,0.0008793732,0.0008640297,0.00104912],"category_scores_gemma":[0.004627154,0.0001979264,0.0005054999,0.0005412875,0.0003641192,0.0007784694,0.0007597719,0.0007106145,0.0006616183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002811663,"about_ca_system_score_gemma":0.0003606397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001682282,"about_ca_topic_score_gemma":0.002750014,"domain_scores_codex":[0.9994645,0.0001338494,0.00004698551,0.0001695248,0.000123126,0.00006217128],"domain_scores_gemma":[0.9985211,0.0006788809,0.0002035691,0.0002936742,0.0002127393,0.00009001385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001394728,0.0004308712,0.1720048,0.0002682092,0.0003158349,0.001502058,0.0003792759,0.06238718,0.01661615,0.001331702,0.01052013,0.7328491],"study_design_scores_gemma":[0.00009035491,0.0004662635,0.0575361,0.0001475716,0.0001587956,0.002887819,0.000510195,0.8875599,0.03478936,0.008983633,0.006815789,0.00005417023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9126465,0.003300438,0.07755888,0.001121437,0.000221301,0.00009369749,0.001036104,0.00123778,0.00278383],"genre_scores_gemma":[0.9614211,0.0004129438,0.0348766,0.0002785673,0.0000976861,0.00003689961,0.001535925,0.00006140327,0.001278986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001682282,"threshold_uncertainty_score":0.007200122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03849775457910067,"score_gpt":0.3198120299745524,"score_spread":0.2813142753954517,"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."}}