{"id":"W2751111689","doi":"10.1017/gheg.2017.9","title":"Developing the science and methods of community engagement for genomic research and biobanking in Africa","year":2017,"lang":"en","type":"article","venue":"Global Health","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; University of Toronto; Wellcome Trust","keywords":"Biobank; Context (archaeology); Engineering ethics; Political science; Community engagement; Public engagement; Public relations; Geography; Engineering; Biology; Bioinformatics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1295861,0.00004790401,0.000195559,0.0000737326,0.002228749,0.00006612264,0.0005300359,0.00006316697,8.787759e-7],"category_scores_gemma":[0.04105537,0.00003336618,0.00001067039,0.0002508489,0.002606794,0.00004509871,0.001229852,0.001303377,3.440896e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006551257,"about_ca_system_score_gemma":0.003316587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002994587,"about_ca_topic_score_gemma":0.001512213,"domain_scores_codex":[0.9974939,0.0009302776,0.000290381,0.00017247,0.0006459774,0.0004669547],"domain_scores_gemma":[0.9906552,0.007699258,0.0001057527,0.0006981046,0.0006907636,0.000150864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002799332,0.0001402946,0.04097179,0.002005484,0.0000155919,0.000001634797,0.005625539,3.55563e-7,0.0008059237,0.5798194,0.0001911067,0.370143],"study_design_scores_gemma":[0.0007492678,0.0006837171,0.6946259,0.0004412866,0.000002462689,0.000004206212,0.002391288,0.0002088959,0.0002712175,0.2987493,0.001832283,0.00004017853],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9508896,0.001203,0.001763989,0.04143939,0.00007242204,0.001078215,0.00001053504,0.000005529753,0.003537305],"genre_scores_gemma":[0.9293748,0.001084543,0.0691222,0.0003604956,0.00001944483,0.00001702076,3.407014e-7,0.000003112272,0.00001800962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6536541,"threshold_uncertainty_score":0.9990702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9263448272265471,"score_gpt":0.7683703905515362,"score_spread":0.1579744366750109,"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."}}