{"id":"W4247377321","doi":"10.21203/rs.2.16121/v5","title":"Geographic Availability To Optometry Services Across Canada: Mapping Distribution, Need And Self-Reported Use","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canadian Association of Optometrists","keywords":"Optometry; Population; Community health; Distribution (mathematics); Census; Medicine; Geography; Health care; Demography; Environmental health; Public health; Nursing; Political science; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0009846395,0.0003352434,0.0003869518,0.005240107,0.002125075,0.001569556,0.001350414,0.0002497185,0.001866941],"category_scores_gemma":[0.004205324,0.0002727438,0.0006030641,0.01147781,0.0007635888,0.0004799183,0.001603743,0.0003729238,0.0002210433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02530301,"about_ca_system_score_gemma":0.03761461,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996293,"about_ca_topic_score_gemma":0.9974788,"domain_scores_codex":[0.9980842,0.0001313585,0.0001648052,0.0002901651,0.0008628414,0.0004666699],"domain_scores_gemma":[0.99585,0.0002803631,0.0006364537,0.0001369695,0.002660334,0.0004358386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004186798,0.00001574886,0.9865536,0.0001256066,0.00008975623,0.00005555521,0.001467396,0.0002690478,0.0001944345,0.0002029964,0.001786159,0.0091979],"study_design_scores_gemma":[0.000002357257,0.000008753046,0.9951423,0.00004998614,0.00002246411,0.00003463079,0.002678974,0.0005033722,0.00007341722,0.00003039571,0.001444071,0.0000092467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747515,0.0008307876,0.0005401759,0.0003403515,0.000007587284,0.0001084373,0.01911963,0.0000375035,0.004264075],"genre_scores_gemma":[0.9939613,0.0004330064,0.0008123968,0.00005483947,0.000003324249,0.00005357356,0.003975949,0.000008490736,0.0006971033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02530301,"threshold_uncertainty_score":0.183587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08965982509834955,"score_gpt":0.444883367613867,"score_spread":0.3552235425155175,"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."}}