{"id":"W2936337436","doi":"10.1038/s41436-019-0482-5","title":"CRISPR in the North American popular press","year":2019,"lang":"en","type":"article","venue":"Genetics in Medicine","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Economics; Université de Montréal; University of Alberta","funders":"Genome Canada","keywords":"CRISPR; Context (archaeology); Social media; Promotion (chess); Internet privacy; Political science; Biology; World Wide Web; Computer science; Genetics; Law; Politics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002607995,0.0001309378,0.0001725629,0.00005626751,0.00001297606,0.000005891833,0.0003214824,0.00004440786,0.00001072522],"category_scores_gemma":[0.00005211245,0.00009593666,0.00002622682,0.0002026664,0.00008135705,8.48718e-7,0.00006329836,0.0001489201,0.000006215973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008823919,"about_ca_system_score_gemma":0.00001373742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001429644,"about_ca_topic_score_gemma":0.0009688311,"domain_scores_codex":[0.9990192,0.00005490841,0.0002253012,0.0002637837,0.0001815463,0.0002552602],"domain_scores_gemma":[0.9993936,0.00001479427,0.00003866146,0.0004919859,0.00002157927,0.00003936509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006236896,0.00009956401,0.8896705,0.00007436238,0.00002750154,0.00002915141,0.001330541,0.01676515,0.07586525,0.00009382877,0.003760994,0.01222078],"study_design_scores_gemma":[0.001453454,0.0008630459,0.8271415,0.00004225834,0.00001993339,0.00002434934,0.0008872333,0.001116927,0.01169917,0.00004116787,0.1563794,0.0003315761],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939035,0.003355323,0.0009077903,0.0003648507,0.0001968161,0.0002581184,0.000002580041,0.000004483032,0.001006541],"genre_scores_gemma":[0.997152,0.001331356,0.0004284955,0.0006081062,0.0002471464,0.00001914217,0.00003953449,0.00001679624,0.0001574619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1526184,"threshold_uncertainty_score":0.3912183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00988191434564925,"score_gpt":0.317002965624726,"score_spread":0.3071210512790767,"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."}}