{"id":"W1481957524","doi":"","title":"Automated measurement of bulbar redness.","year":2002,"lang":"en","type":"article","venue":"PubMed","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial intelligence; Mathematics; Pixel; Grading (engineering); RGB color model; Pattern recognition (psychology); Computer vision; Medicine; Computer science; Statistics","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":[0.001468212,0.0003852583,0.0003928589,0.001640421,0.0001846834,0.000551283,0.0004686601,0.0003877847,0.003658264],"category_scores_gemma":[0.006373193,0.0002152452,0.0002110524,0.0006674356,0.0002624142,0.0005103155,0.000534322,0.000308326,0.001399786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002999716,"about_ca_system_score_gemma":0.0002326287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001255247,"about_ca_topic_score_gemma":0.001774034,"domain_scores_codex":[0.9982273,0.000498975,0.00009089741,0.0003909224,0.000730739,0.00006118677],"domain_scores_gemma":[0.9961768,0.001261407,0.0009305821,0.000478522,0.001048624,0.0001040731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009409182,0.0003137406,0.3045467,0.0008913988,0.000302077,0.0001365839,0.0002426002,0.002788181,0.1308223,0.0004837661,0.004603443,0.5539284],"study_design_scores_gemma":[0.00006324546,0.0006720439,0.9076602,0.0001265629,0.0001345144,0.001738939,0.000136559,0.0298335,0.05323726,0.0007286735,0.005596306,0.0000722702],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7817459,0.005044599,0.1939292,0.0002142301,0.0001154199,0.000603623,0.00325877,0.003892319,0.01119585],"genre_scores_gemma":[0.9110348,0.0006888448,0.08363767,0.0001638191,0.0000603469,0.0002784208,0.001134706,0.0001437432,0.002857676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003658264,"threshold_uncertainty_score":0.01223814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04990646110441783,"score_gpt":0.2234764710761342,"score_spread":0.1735700099717164,"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."}}