{"id":"W2112237420","doi":"10.1155/2014/246096","title":"Advance in ERG Analysis: From Peak Time and Amplitude to Frequency, Power, and Energy","year":2014,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Retinal Development and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; McGill University; Montreal Children's Hospital","funders":"Canadian Institutes of Health Research","keywords":"Erg; Time domain; Amplitude; Frequency domain; Computer science; Artificial intelligence; Wavelet; Electroretinography; Pattern recognition (psychology); Algorithm; Physics; Optics; Computer vision; Retina","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003567428,0.00007250261,0.00008690222,0.0003272489,0.00003609903,0.00004797679,0.0001778388,0.00005763814,0.00007790387],"category_scores_gemma":[0.0002258294,0.00006811394,0.00002338907,0.0002455025,0.00008787931,0.00000685207,0.000192702,0.00005318486,0.00001153125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001749669,"about_ca_system_score_gemma":0.00002917372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003954143,"about_ca_topic_score_gemma":0.0004659293,"domain_scores_codex":[0.9990379,0.00007775222,0.0001247591,0.000319161,0.0002588595,0.0001815869],"domain_scores_gemma":[0.9996141,0.00003939954,0.00001908274,0.0001198424,0.0001033842,0.0001042173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002430843,0.00008900052,0.09225536,0.000004345922,0.0003314263,0.000006739866,0.0001339003,0.00001547794,0.8902637,0.002529869,0.003503926,0.01062313],"study_design_scores_gemma":[0.001047872,0.0002873141,0.6744252,0.00002762495,0.00001185986,0.000002824364,0.0000959708,0.0008453474,0.01197739,0.003792981,0.3071623,0.0003232757],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906993,0.0005298456,0.001161693,0.001354145,0.00008163434,0.00004653337,0.00003094039,0.000004430672,0.006091457],"genre_scores_gemma":[0.9960551,0.0003148438,0.001635357,0.0001607658,0.00007718516,0.00002038171,0.0002983291,0.000006418283,0.001431595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8782864,"threshold_uncertainty_score":0.2777606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01056831720044734,"score_gpt":0.3145518677307463,"score_spread":0.303983550530299,"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."}}