{"id":"W4312822149","doi":"10.12968/opti.2018.1.6857","title":"Meibography: an overview","year":2018,"lang":"en","type":"article","venue":"Optician","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Geography; Computer science; Data science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007755242,0.00007484287,0.0001331215,0.00004675581,0.00005423603,0.00001446246,0.00005349998,0.00004745684,0.0005299348],"category_scores_gemma":[0.0000116995,0.0000628741,0.00006902303,0.0001421857,0.00004850168,0.00007351054,0.00001313289,0.00006593148,0.0004951472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001030443,"about_ca_system_score_gemma":0.00003139632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005714481,"about_ca_topic_score_gemma":0.0001151651,"domain_scores_codex":[0.9994599,0.00001527717,0.00008659263,0.000142193,0.0001240353,0.0001720203],"domain_scores_gemma":[0.9994531,0.000005202379,0.00001869614,0.0003248184,0.00006884745,0.0001293347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004737535,0.001405111,0.5360733,0.0002823581,0.0006449737,0.0005197395,0.002807565,9.434227e-7,0.06178554,0.09839617,0.002536419,0.2950742],"study_design_scores_gemma":[0.001543669,0.00290667,0.442315,0.0002497707,0.0003233468,0.00002513837,0.0005286291,0.0003779231,0.01255363,0.0009150431,0.537872,0.0003892301],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9421493,0.00105194,0.00005618602,0.000767361,0.0001804264,0.0001223742,0.00000173625,0.00007455949,0.05559606],"genre_scores_gemma":[0.9932046,0.0001276415,0.002461313,0.00301262,0.0004138254,0.000002986083,0.000008783622,0.0000163922,0.0007518647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5353356,"threshold_uncertainty_score":0.6364281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04531966552918585,"score_gpt":0.3354057194285738,"score_spread":0.2900860538993879,"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."}}