{"id":"W3089653673","doi":"10.1016/s2589-7500(20)30240-5","title":"A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability","year":2020,"lang":"en","type":"review","venue":"The Lancet Digital Health","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":333,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Medical Research Council; National Institute for Health and Care Research; Seva Foundation; Fred Hollows Foundation; Queen Elizabeth Diamond Jubilee Trust; Moorfields Eye Charity; Wellcome Trust","keywords":"Metadata; Computer science; Usability; Population; Data science; MEDLINE; Information retrieval; World Wide Web; Medicine; Environmental health; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.001720574,0.0003612932,0.003695373,0.00003701368,0.0001047864,0.0001855406,0.0006587027,0.00006047307,0.00009574474],"category_scores_gemma":[0.004374026,0.0002038313,0.0004716618,0.0007649365,0.0002764123,0.0002100505,0.0004927306,0.0002510215,0.00001781508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001918154,"about_ca_system_score_gemma":0.001289295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002350332,"about_ca_topic_score_gemma":0.00000432208,"domain_scores_codex":[0.9971505,0.0002436566,0.0009930739,0.0007750097,0.0003305711,0.0005071753],"domain_scores_gemma":[0.9971886,0.0003188753,0.0004369268,0.00110609,0.0001241093,0.0008254037],"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":[0.000046254,0.00005311977,0.006451315,0.2226394,0.0001044701,0.000009397404,0.00000574084,4.20686e-8,6.307189e-9,0.00007192443,0.2370361,0.5335822],"study_design_scores_gemma":[0.0001911465,0.0001730368,0.0001003455,0.02609447,0.0004590211,0.0003276729,0.00000716922,0.00001592703,3.721723e-8,0.0002288315,0.9722394,0.0001629701],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001997079,0.9537843,0.0000331311,0.03365479,0.00004476093,0.002141806,0.009116317,0.00004418834,0.001160767],"genre_scores_gemma":[0.0001056405,0.9874171,0.0003929814,0.009396528,0.0002822199,0.000121049,0.002206819,0.000021714,0.00005595684],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7352033,"threshold_uncertainty_score":0.8311998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1755210722985354,"score_gpt":0.4731320854712138,"score_spread":0.2976110131726785,"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."}}