{"id":"W2026533610","doi":"10.1097/opx.0000000000000340","title":"Comparative Study of Lens Solutions' Ability to Remove Tear Constituents","year":2014,"lang":"en","type":"article","venue":"Optometry and Vision Science","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Johnson and Johnson Vision Care; Natural Sciences and Engineering Research Council of Canada; Abbott Medical Optics; University of Waterloo","keywords":"Lens (geology); Atomic force microscopy; Silicone hydrogel; Chemistry; Materials science; Surface roughness; Adsorption; Biomedical engineering; Contact lens; Nanotechnology; Chromatography; Optics; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004469476,0.0005000932,0.0002770503,0.0003416134,0.0002090941,0.0003626238,0.0002030015,0.0003561131,0.001469586],"category_scores_gemma":[0.0008361134,0.0001346886,0.0003162774,0.0002330068,0.0001822576,0.0003972572,0.0002600751,0.0002957286,0.0002365804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002302168,"about_ca_system_score_gemma":0.0002434695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008141723,"about_ca_topic_score_gemma":0.0008595887,"domain_scores_codex":[0.9995422,0.00008549716,0.00005104947,0.00008689913,0.0001614714,0.00007293054],"domain_scores_gemma":[0.999395,0.0002017672,0.0001072746,0.00004757556,0.000206348,0.00004203147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001398892,0.00002570055,0.0004490616,0.0001093789,0.00001868083,0.00002932283,0.00004163137,0.00003427705,0.9955915,0.00001809167,0.0000235835,0.003518871],"study_design_scores_gemma":[0.000006611853,0.0006927749,0.005189602,0.00001089757,0.00003746052,0.0001007995,0.00005543888,0.0002557412,0.9923208,0.00001677391,0.001305103,0.000007827404],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902846,0.005745303,0.002280509,0.0000680743,0.00004587051,0.00004828521,0.0001796021,0.00004017591,0.001307553],"genre_scores_gemma":[0.9878541,0.002708836,0.006824208,0.0001144679,0.00003240116,0.00006909874,0.0005245965,0.00004012686,0.001832263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001469586,"threshold_uncertainty_score":0.004916251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0375034384657734,"score_gpt":0.4375648577394077,"score_spread":0.4000614192736343,"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."}}