{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002749812,0.0002327142,0.0005676989,0.000108677,0.0001461313,0.0001035564,0.0006339116,0.0009336113,0.01870374],"category_scores_gemma":[0.01355477,0.0001888357,0.0001979247,0.0002203027,0.000857761,0.00007152068,0.0004193485,0.002300757,0.01528984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002675247,"about_ca_system_score_gemma":0.004383276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001614771,"about_ca_topic_score_gemma":0.0002411624,"domain_scores_codex":[0.9958059,0.0002327585,0.0008079539,0.0005742717,0.001873943,0.0007051454],"domain_scores_gemma":[0.9902296,0.006722742,0.0001199348,0.0009097892,0.0004206735,0.001597276],"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":[0.003430271,0.009493693,0.1027668,0.006968579,0.002558588,0.002431067,0.004544032,0.0003969721,0.06116103,0.1078222,0.2824039,0.4160228],"study_design_scores_gemma":[0.0276438,0.007946189,0.1204648,0.003052275,0.0007009921,0.0007838391,0.001195467,0.1520017,0.003264207,0.1585584,0.5215098,0.00287851],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9123899,0.001104496,0.002753534,0.02220105,0.0005508595,0.004049302,0.00002857843,0.0002990821,0.05662323],"genre_scores_gemma":[0.866594,0.004129095,0.04069759,0.01396131,0.003104727,0.0007204228,0.0002542632,0.0002720867,0.07026652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4131443,"threshold_uncertainty_score":0.9995772,"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."}}