{"id":"W2006195944","doi":"10.1186/1755-8794-6-19","title":"Genotype-driven recruitment: a strategy whose time has come?","year":2013,"lang":"en","type":"article","venue":"BMC Medical Genomics","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Norges Forskningsråd; European Commission","keywords":"Biobank; Genotyping; Genotype; Data science; Psychology; Public relations; Engineering ethics; Political science; Biology; Computer science; Bioinformatics; Genetics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3660834,0.001623616,0.003061205,0.002258028,0.006408097,0.01485134,0.006798266,0.01564509,0.02160494],"category_scores_gemma":[0.4713781,0.001080335,0.001965255,0.002772614,0.01052506,0.02523516,0.01340405,0.01820494,0.009658596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007295982,"about_ca_system_score_gemma":0.05555248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005689143,"about_ca_topic_score_gemma":0.009131205,"domain_scores_codex":[0.7255016,0.2369291,0.009977787,0.007010131,0.0150509,0.005530473],"domain_scores_gemma":[0.4280163,0.3809124,0.02816135,0.04697494,0.06192471,0.05401035],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00151267,0.0006846837,0.0228148,0.00427214,0.0004039882,0.001963166,0.03610307,0.0008989095,0.001813807,0.12196,0.3622122,0.4453606],"study_design_scores_gemma":[0.001111705,0.001795626,0.01496854,0.02302843,0.000464977,0.003502713,0.0459526,0.00405825,0.001561911,0.2702791,0.6326629,0.0006132735],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.006289535,0.004971528,0.0366413,0.9340091,0.01193505,0.0009680918,0.0001611732,0.0002438641,0.00478045],"genre_scores_gemma":[0.1259006,0.006970338,0.1443977,0.692704,0.008707731,0.01154608,0.000516049,0.000636851,0.008620711],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.6339166,"threshold_uncertainty_score":0.781732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5501003997644451,"score_gpt":0.5105790043000419,"score_spread":0.03952139546440325,"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."}}