{"id":"W3005614734","doi":"10.1016/j.tibtech.2019.12.002","title":"Options to Reform the European Union Legislation on GMOs: Scope and Definitions","year":2020,"lang":"en","type":"article","venue":"Trends in biotechnology","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung; Stiftelsen för Miljöstrategisk Forskning","keywords":"Scope (computer science); Legislation; European union; Political science; Coherence (philosophical gambling strategy); Genetically modified organism; Business; Law and economics; International trade; Law; Economics; Computer science; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002649553,0.00007325318,0.00007026631,0.00004875994,0.0001411258,0.00002809442,0.000254162,0.0001022639,0.0001220486],"category_scores_gemma":[0.00006550438,0.00002662307,0.00001638902,0.0009302585,0.0001161752,0.00002242969,0.0001848547,0.0002431438,0.0001577289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002630353,"about_ca_system_score_gemma":0.000002162296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001200155,"about_ca_topic_score_gemma":0.0009668402,"domain_scores_codex":[0.9991889,0.0001803835,0.0001150072,0.0002353302,0.0000925023,0.0001878617],"domain_scores_gemma":[0.9997876,0.00004586837,0.00001734956,0.00007376666,0.00001377636,0.00006165854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000008003533,0.00003340166,0.0001347423,7.282981e-7,0.000002194151,0.000004028966,0.00008756253,0.00002063089,0.2093417,0.02479413,0.0003673055,0.7652056],"study_design_scores_gemma":[0.0003692851,0.002348951,0.8811752,0.00002588927,0.000008468075,0.00001706972,0.0008993148,0.0002211077,0.03074875,0.003665994,0.08018111,0.0003388815],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6827036,0.00005121372,0.00005481712,0.2970678,0.0000201468,0.0001048563,0.00001845733,0.000112524,0.01986652],"genre_scores_gemma":[0.9986869,0.0001720389,0.0003919055,0.0006126484,0.00004901096,0.000008642573,0.00002294348,0.000001190461,0.00005476453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8810405,"threshold_uncertainty_score":0.2027338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09297949534977978,"score_gpt":0.2734753741431435,"score_spread":0.1804958787933637,"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."}}