{"id":"W3183288317","doi":"10.1002/wmh3.469","title":"Access to genetic testing for rare diseases: Existing gaps in public‐facing information","year":2021,"lang":"en","type":"article","venue":"World Medical & Health Policy","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Genetic testing; Reimbursement; Context (archaeology); CLARITY; Public health; Medicine; Government (linguistics); Rare disease; Health care; Business; Public policy; Disease; Internet privacy; Public relations; Political science; Economic growth; Nursing; Pathology; Computer science; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0003579903,0.0001247329,0.0001770954,0.0002473475,0.0001616424,0.00008574568,0.0002573675,0.00008352633,0.00003293855],"category_scores_gemma":[0.0084115,0.0001360233,0.00004519551,0.0009859275,0.00003653611,0.00001980467,0.0002524609,0.0001341888,0.000007555709],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003789786,"about_ca_system_score_gemma":0.005976382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000421996,"about_ca_topic_score_gemma":0.002304963,"domain_scores_codex":[0.9983023,0.00008816752,0.0005200466,0.0002814818,0.0002758156,0.0005321857],"domain_scores_gemma":[0.9987199,0.0001106835,0.0001260723,0.0002748736,0.0002175917,0.0005508931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007306711,0.0001674248,0.05871696,0.001281228,0.00004627804,0.0000164628,0.001204832,0.001459616,0.001546513,0.001695507,0.0792571,0.854535],"study_design_scores_gemma":[0.001617516,0.0001677424,0.06215962,0.0003769827,0.000009018305,0.00003690279,0.00027816,0.001308026,0.00169747,0.0005477078,0.9314354,0.0003654581],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4937451,0.008922617,0.06858322,0.4084014,0.001971839,0.004068528,0.0006659993,0.0002163933,0.01342484],"genre_scores_gemma":[0.9108407,0.00009960851,0.01853163,0.06744476,0.001737358,0.0004964966,0.0005268319,0.00003298661,0.0002896571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8541695,"threshold_uncertainty_score":0.9999411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0572080731186063,"score_gpt":0.419624059164425,"score_spread":0.3624159860458187,"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."}}