{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001141599,0.00007216991,0.0002415459,0.0002066079,0.0002104656,0.00002335382,0.0001084377,0.00002381608,0.00002310792],"category_scores_gemma":[0.0003365556,0.00005613111,0.00002295892,0.001009253,0.0003461611,0.0001957909,0.0001278352,0.00008408228,0.00003015317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002278223,"about_ca_system_score_gemma":0.0000526607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002521848,"about_ca_topic_score_gemma":0.000003613381,"domain_scores_codex":[0.9988368,0.00005021391,0.0001754219,0.0003107919,0.00045219,0.0001745483],"domain_scores_gemma":[0.9991608,0.00008796092,0.00004735146,0.0003248628,0.0002223238,0.0001566462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001448607,0.001030298,0.8711144,0.00003862813,0.00001295211,0.000002071679,0.002405006,0.00002280639,0.1194092,0.00058289,0.00004053753,0.005196312],"study_design_scores_gemma":[0.0008758486,0.001557027,0.9873783,0.00006671918,0.00002247294,0.000002837689,0.002526456,0.0008209108,0.006002247,0.00001614931,0.0006497295,0.00008127897],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946738,0.00002856118,0.0008103523,0.0001634875,0.00008996586,0.0003297098,0.000002184007,0.00001242075,0.0038895],"genre_scores_gemma":[0.9989813,0.000003787179,0.0007944446,0.0001492073,0.00001121682,0.000001933854,3.176945e-7,0.000001783065,0.00005598419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1162639,"threshold_uncertainty_score":0.228896,"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."}}