{"id":"W2514639543","doi":"10.1097/opx.0000000000000983","title":"Understanding and Treating Myopia: Yesterday, Today, and Tomorrow","year":2016,"lang":"en","type":"editorial","venue":"Optometry and Vision Science","topic":"Ophthalmology and Visual Impairment Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Yesterday; Honor; China; Library science; Media studies; Political science; Optometry; Medicine; History; Sociology; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001209032,0.0002730019,0.0005046606,0.000516015,0.0008346998,0.0001576028,0.0001057064,0.0003499288,0.00002553298],"category_scores_gemma":[0.001234133,0.0001795637,0.0000324887,0.0004921028,0.001679722,0.0004014159,0.0004644873,0.0003652604,0.000004648711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000101203,"about_ca_system_score_gemma":0.0001069243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005682347,"about_ca_topic_score_gemma":3.627765e-7,"domain_scores_codex":[0.9979393,0.00004177503,0.0002483821,0.000748147,0.0006340409,0.0003883321],"domain_scores_gemma":[0.9982209,0.001043741,0.0001424656,0.000206128,0.0001178179,0.0002689257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001160312,0.000498467,0.5179201,0.003205886,0.0002451505,0.0002657202,0.002285932,6.49625e-8,0.005648234,0.0006735706,0.4402083,0.02788826],"study_design_scores_gemma":[0.02444054,0.0410074,0.6764163,0.02539658,0.001680533,0.002197821,0.007890442,0.0005807803,0.001537137,0.003615955,0.210975,0.004261552],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7705252,0.002214253,0.0003372463,0.0009013645,0.2218053,0.0004170859,0.00005642129,0.00005927619,0.003683819],"genre_scores_gemma":[0.9291298,0.001984141,0.0003054618,0.00006311439,0.06609584,0.000006886718,0.000006921693,0.00001833801,0.002389479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2292333,"threshold_uncertainty_score":0.7322397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05166418479384635,"score_gpt":0.47854219580444,"score_spread":0.4268780110105936,"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."}}