{"id":"W3090467525","doi":"10.1016/j.gfs.2020.100440","title":"Regulatory barriers to improving global food security","year":2020,"lang":"en","type":"article","venue":"Global Food Security","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canada First Research Excellence Fund","keywords":"Food security; Business; Agriculture; Emerging technologies; Crop; Biotechnology; Food processing; Abiotic component; Natural resource economics; Marketing; Risk analysis (engineering); Computer science; Economics; Biology; Agronomy; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001285233,0.0003186252,0.0002526873,0.00001214675,0.0001214775,0.00005393508,0.0004105941,0.0002546241,0.00003332498],"category_scores_gemma":[0.0002765421,0.0003630089,0.0001926581,0.0003000199,0.00005338169,0.000007231049,0.0004375348,0.0001421456,0.0000238897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008455258,"about_ca_system_score_gemma":0.0001800943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004459293,"about_ca_topic_score_gemma":0.000286777,"domain_scores_codex":[0.9981199,0.00004915714,0.0002829346,0.0007172882,0.000274483,0.0005562347],"domain_scores_gemma":[0.998356,0.000003572009,0.0000548599,0.0004678038,0.00008864018,0.001029067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.008140163,0.001333725,0.1491352,0.003856109,0.005286428,0.0002656981,0.01328826,0.01911575,0.4142375,0.1045933,0.224563,0.05618488],"study_design_scores_gemma":[0.00799582,0.02542595,0.02213602,0.0001335903,0.0004676707,0.0002768539,0.003893227,0.004971184,0.5365212,0.02509011,0.366843,0.006245418],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902884,0.001830268,0.00380035,0.0004525434,0.000403733,0.0003369725,0.0007772185,0.00009877248,0.002011737],"genre_scores_gemma":[0.9970623,0.00001573105,0.0004140119,0.001870056,0.0005358748,0.00001635963,0.00006205768,0.00001987757,0.000003727235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.14228,"threshold_uncertainty_score":0.9998822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005911610598903976,"score_gpt":0.2568364683481112,"score_spread":0.2509248577492072,"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."}}