{"id":"W2979819720","doi":"10.1016/j.exer.2019.107831","title":"Non-invasive in vivo measurement of ocular rigidity: Clinical validation, repeatability and method improvement","year":2019,"lang":"en","type":"article","venue":"Experimental Eye Research","topic":"Glaucoma and retinal disorders","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Montréal; Hôpital Maisonneuve-Rosemont","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Glaucoma Research Society of Canada","keywords":"Repeatability; Intraclass correlation; Optical coherence tomography; Glaucoma; Choroid; Ophthalmology; Mathematics; Biomedical engineering; Medicine; Reproducibility; Statistics; Optics; Physics; Retina","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":[0.01602094,0.001316497,0.00128517,0.00127824,0.0006037272,0.001660689,0.001366471,0.001894508,0.001671023],"category_scores_gemma":[0.03259574,0.0008704151,0.0006473193,0.0008952419,0.001728658,0.001185937,0.001266704,0.00121977,0.0008846123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004706242,"about_ca_system_score_gemma":0.0008937083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001533129,"about_ca_topic_score_gemma":0.003160475,"domain_scores_codex":[0.9785618,0.01166709,0.001251584,0.002928626,0.005303794,0.0002872178],"domain_scores_gemma":[0.9515757,0.02977208,0.003561446,0.007303913,0.007281552,0.0005053143],"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":[0.0131207,0.002446672,0.2108826,0.002690644,0.00154875,0.0002947856,0.00267988,0.004531859,0.4274212,0.001954193,0.002855686,0.3295732],"study_design_scores_gemma":[0.001144496,0.01365838,0.6996435,0.0004438368,0.002120295,0.00620862,0.0008866671,0.04284375,0.2196665,0.002255848,0.01077047,0.0003576297],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6970898,0.01541034,0.2744683,0.0008241496,0.00103615,0.001616687,0.001514342,0.001342112,0.006698149],"genre_scores_gemma":[0.9094683,0.002132756,0.08349797,0.000440855,0.0002872401,0.0005628762,0.0006817418,0.0003347104,0.002593698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01602094,"threshold_uncertainty_score":0.08472782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08522444357295593,"score_gpt":0.4630621309251814,"score_spread":0.3778376873522255,"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."}}