{"id":"W2910141964","doi":"10.2147/mder.s186529","title":"Undermining a common language: smartphone applications for eye emergencies","year":2019,"lang":"en","type":"article","venue":"Medical Devices Evidence and Research","topic":"Ophthalmology and Visual Health Research","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Optometry; Medicine; Medical emergency; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01994292,0.001038268,0.002483107,0.01338025,0.001019738,0.006765101,0.00227666,0.004483427,0.01014401],"category_scores_gemma":[0.1211329,0.0006187037,0.003224392,0.01367112,0.004385169,0.008303346,0.003452433,0.003290087,0.001644542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004897874,"about_ca_system_score_gemma":0.0142895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01226283,"about_ca_topic_score_gemma":0.02444074,"domain_scores_codex":[0.9662427,0.01283983,0.01131733,0.001787241,0.007144582,0.0006683549],"domain_scores_gemma":[0.7937875,0.1372509,0.046286,0.002468103,0.01855131,0.001656162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005818211,0.00006522989,0.00525245,0.4992505,0.0009204913,0.001109369,0.002329219,0.0001337203,0.0007755543,0.005117607,0.04974651,0.4347175],"study_design_scores_gemma":[0.0002313084,0.0003038161,0.02104509,0.7372811,0.003457274,0.0045131,0.003872065,0.0001246686,0.0006152701,0.003350363,0.2251123,0.00009376914],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.003008062,0.9744476,0.0003766485,0.01558346,0.001761045,0.0001224771,0.0005109007,0.00002925292,0.004160587],"genre_scores_gemma":[0.0402072,0.9341219,0.001838855,0.01949789,0.002121674,0.0002453041,0.0005639291,0.00004078557,0.001362457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01994292,"threshold_uncertainty_score":0.1054695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3100867127835325,"score_gpt":0.6257157971289605,"score_spread":0.315629084345428,"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."}}