{"id":"W240095210","doi":"10.1097/opx.0000000000000618","title":"Competitive Effects from an Artificial Tear Solution to Protein Adsorption","year":2015,"lang":"en","type":"article","venue":"Optometry and Vision Science","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adsorption; Lysozyme; Chemistry; Protein adsorption; Ionic strength; Silicone hydrogel; Albumin; Contact lens; Chromatography; Biophysics; Chemical engineering; Biochemistry; Organic chemistry; Aqueous solution; Biology; Optics","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":[0.001109931,0.001350916,0.0006653947,0.0003798523,0.0004009322,0.0008996512,0.001048866,0.0006641504,0.002907873],"category_scores_gemma":[0.003277835,0.0005020102,0.0006538732,0.0002344248,0.0005498456,0.0006730138,0.0009958522,0.000864287,0.000632042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009299669,"about_ca_system_score_gemma":0.0007386541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003632906,"about_ca_topic_score_gemma":0.00308444,"domain_scores_codex":[0.9965079,0.0005864034,0.0002003062,0.0005930014,0.001689019,0.0004233799],"domain_scores_gemma":[0.9967008,0.001765704,0.0003475408,0.0002917784,0.0007391989,0.0001550418],"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":[0.000179494,0.00003182604,0.0003427353,0.0001799687,0.00002382714,0.00005887705,0.00004578628,0.00007400113,0.9970163,0.00004537052,0.00005595928,0.001945905],"study_design_scores_gemma":[0.00001174438,0.0005825451,0.002898563,0.00001650476,0.00002787776,0.000254752,0.00004077719,0.001494889,0.9932556,0.0000265931,0.001377614,0.00001259218],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.972438,0.007212358,0.01569892,0.0002941244,0.0002132109,0.0002791708,0.0002600837,0.0002149979,0.003389197],"genre_scores_gemma":[0.9860803,0.001515,0.008169685,0.0002554765,0.00006440443,0.0001756546,0.0003608128,0.00008677977,0.003291831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003632906,"threshold_uncertainty_score":0.009727776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02157718788716876,"score_gpt":0.4021015606109789,"score_spread":0.3805243727238101,"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."}}