{"id":"W4309246368","doi":"10.1038/s41433-022-02307-9","title":"Current uses of artificial intelligence in the analysis of biofluid markers involved in corneal and ocular surface diseases: a systematic review","year":2022,"lang":"en","type":"review","venue":"Eye","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Public Health Ontario; Toronto Public Health; Queen's University; Western University","funders":"","keywords":"Medicine; Biomarker; Biomarker discovery; Bioinformatics; Proteomics; Biology; Gene","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":[0.001413004,0.0002747781,0.003825658,0.000396825,0.00001872003,0.000009066753,0.0002716214,0.00007106273,0.0001129066],"category_scores_gemma":[0.0006078474,0.0001740594,0.0007837481,0.002446074,0.00007738864,0.00003047777,0.00008692453,0.0003381343,0.000002672072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009176987,"about_ca_system_score_gemma":0.0002513841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001413825,"about_ca_topic_score_gemma":0.0001405592,"domain_scores_codex":[0.9963642,0.001155834,0.001510147,0.0003215204,0.0004750901,0.0001732219],"domain_scores_gemma":[0.9980285,0.0005530589,0.0006117644,0.0007072636,0.0000438276,0.00005558948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00001804765,0.0002497205,0.003831301,0.9464187,0.00102994,0.00005233403,0.000180453,0.000003320692,4.33768e-7,0.00005479332,0.000006410021,0.04815452],"study_design_scores_gemma":[0.0001297326,0.0002114653,0.0007509966,0.8975278,0.07759719,0.000002907097,0.001270279,0.0004637732,0.000001222693,0.00001549659,0.02164415,0.0003850255],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003135092,0.9941528,0.00001520592,0.00002352492,0.00005036346,0.002508358,0.0001016022,0.000005215785,0.000007821917],"genre_scores_gemma":[0.002246062,0.9973916,0.00001383628,0.0000422632,0.000007171422,0.0001152319,0.0001629599,0.00001647515,0.000004411622],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.07656725,"threshold_uncertainty_score":0.7097936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05967921921351873,"score_gpt":0.3560435561541034,"score_spread":0.2963643369405847,"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."}}