{"id":"W2181801152","doi":"10.1503/cmaj.150577","title":"Difficulty with right–left discrimination: A clinical problem?","year":2015,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Names, Identity, and Discrimination Research","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Wilson Centre; University Health Network","funders":"","keywords":"Left and right; Population; Medicine; Right-to-left; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003507293,0.0005293715,0.001032837,0.001960785,0.003997826,0.002449525,0.001693724,0.003372794,0.008122672],"category_scores_gemma":[0.03613923,0.000349908,0.0002197429,0.002621764,0.002800348,0.004893048,0.002122069,0.003086941,0.002122659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001555348,"about_ca_system_score_gemma":0.00240816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007369951,"about_ca_topic_score_gemma":0.01546535,"domain_scores_codex":[0.9964645,0.0007747615,0.0004665724,0.0006246139,0.001211685,0.0004578454],"domain_scores_gemma":[0.9901727,0.003235809,0.002557774,0.0004461583,0.002151014,0.001436472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002564593,0.0005747471,0.4358863,0.0006008759,0.00006489949,0.08048939,0.02604736,0.0003225752,0.001402676,0.01862218,0.1752601,0.2604725],"study_design_scores_gemma":[0.0001052562,0.0002652996,0.1210446,0.003153181,0.0001056472,0.6240752,0.08777212,0.003216025,0.001062192,0.07493022,0.08399076,0.0002794274],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5481913,0.02332067,0.01282714,0.3036731,0.004046351,0.0002728858,0.0008604841,0.0003896201,0.1064184],"genre_scores_gemma":[0.9559546,0.006461588,0.004776177,0.02598679,0.002566252,0.00007236749,0.0002238805,0.000107163,0.003851086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008122672,"threshold_uncertainty_score":0.0271731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04606159382353048,"score_gpt":0.3683943312076819,"score_spread":0.3223327373841514,"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."}}