{"id":"W4405838591","doi":"10.1097/opx.0000000000002207","title":"THANK YOU! To <i>Optometry &amp; Vision Science</i> reviewers and editors","year":2024,"lang":"en","type":"article","venue":"Optometry and Vision Science","topic":"Ocular and Laser Science Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Optometry; Vision science; Ophthalmology; Psychology; Medicine; Computer science; Artificial intelligence","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":[0.03433633,0.003087817,0.004029627,0.006298999,0.003541004,0.01964692,0.004439831,0.00830207,0.0827032],"category_scores_gemma":[0.2579605,0.001463348,0.002933731,0.003340771,0.002714294,0.009453804,0.004369824,0.01156674,0.1767026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002778208,"about_ca_system_score_gemma":0.01045096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001646949,"about_ca_topic_score_gemma":0.003067832,"domain_scores_codex":[0.9676567,0.005984426,0.004122306,0.003450559,0.01742145,0.001364599],"domain_scores_gemma":[0.5085316,0.03034026,0.02634754,0.01094915,0.3805078,0.04332377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002520009,0.000009614267,0.0001420685,0.0002979083,0.00001151291,0.00006381599,0.00007031739,0.00001596343,0.0001084873,0.0001543326,0.9850985,0.01400227],"study_design_scores_gemma":[0.00003432366,0.00003572587,0.0003569078,0.0005515591,0.00002824637,0.0003401697,0.0002940514,0.00007946429,0.0001378108,0.0007191071,0.9973732,0.00004945417],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0003248233,0.01233932,0.003155452,0.1582418,0.8162216,0.0004470045,0.0004784046,0.002010875,0.006780832],"genre_scores_gemma":[0.003449085,0.01861574,0.007390132,0.1433505,0.7328743,0.001371088,0.001128502,0.002136212,0.08968445],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.0827032,"threshold_uncertainty_score":0.2766698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02179116829711874,"score_gpt":0.4974809274879881,"score_spread":0.4756897591908694,"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."}}