{"id":"W2748031140","doi":"","title":"Development of a novel, objective metric to determine tear film stability","year":2017,"lang":"en","type":"article","venue":"Investigative Ophthalmology & Visual Science","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Metric (unit); Stability (learning theory); Ophthalmology; Mathematics; Computer science; Materials science; Medicine; Engineering; Operations management; Machine learning","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":[0.00225746,0.001111445,0.0007008968,0.002599721,0.0004398933,0.001973841,0.0009565254,0.001075621,0.00155994],"category_scores_gemma":[0.004830588,0.0003738598,0.0003970292,0.001079763,0.0004684803,0.002335316,0.001074167,0.001021644,0.0006683236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006799825,"about_ca_system_score_gemma":0.001206598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001390195,"about_ca_topic_score_gemma":0.003221282,"domain_scores_codex":[0.9979509,0.0003289105,0.0001697031,0.0002922814,0.001198967,0.00005939405],"domain_scores_gemma":[0.995227,0.0009652727,0.0006262066,0.0002287323,0.002779919,0.000172938],"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":[0.0004000011,0.0003284278,0.03088333,0.0009189422,0.0001996117,0.0002115068,0.0002510731,0.002023001,0.6544895,0.003611732,0.005365777,0.301317],"study_design_scores_gemma":[0.0001358594,0.001888659,0.05858187,0.0002354841,0.0004067623,0.003981224,0.000489362,0.1001686,0.7932745,0.002122538,0.03838175,0.0003334262],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1383086,0.008346176,0.8397878,0.0007075684,0.0008676084,0.0006105825,0.001174497,0.00149708,0.008700026],"genre_scores_gemma":[0.358865,0.003405087,0.6285212,0.0006303847,0.0003371832,0.0008287428,0.0009692284,0.0002703634,0.006172853],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002599721,"threshold_uncertainty_score":0.01193875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08944047558422781,"score_gpt":0.3733989173667278,"score_spread":0.2839584417825,"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."}}