{"id":"W1970700295","doi":"10.1016/j.yrtph.2015.03.008","title":"Genomics in the land of regulatory science","year":2015,"lang":"en","type":"article","venue":"Regulatory Toxicology and Pharmacology","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Food Inspection Agency","funders":"U.S. Food and Drug Administration; Canadian Food Inspection Agency; Génome Québec; McGill University; University of Arkansas for Medical Sciences; Public Health Agency of Canada; University of Arkansas","keywords":"Regulatory science; Context (archaeology); Transparency (behavior); Genomics; Traceability; Process (computing); Risk analysis (engineering); Computer science; Business; Management science; Engineering; Medicine; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04404706,0.000761693,0.001445348,0.002607567,0.005541591,0.01320966,0.001586622,0.01121624,0.006217985],"category_scores_gemma":[0.02800181,0.0005086712,0.001024279,0.001957411,0.059488,0.01729306,0.008013457,0.02148906,0.001131183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01135001,"about_ca_system_score_gemma":0.01547305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005450476,"about_ca_topic_score_gemma":0.002907711,"domain_scores_codex":[0.973469,0.01677402,0.0007524084,0.002825467,0.004459969,0.001719082],"domain_scores_gemma":[0.9721885,0.01964064,0.001079584,0.002715247,0.002541359,0.001834729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002063211,0.00001858381,0.0001335764,0.00006762268,0.000007851743,0.00005359658,0.000914875,0.0003448143,0.0002619054,0.9783166,0.007901601,0.01195838],"study_design_scores_gemma":[0.00001836527,0.00003777869,0.0002214777,0.00026395,0.000006758267,0.00005491318,0.0007664933,0.000287912,0.0002966013,0.7966373,0.2013874,0.00002108287],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.00828406,0.05300055,0.04060198,0.7398528,0.00972339,0.00009053443,0.0001071845,0.0002359767,0.1481035],"genre_scores_gemma":[0.5321015,0.05051889,0.04558661,0.3163456,0.01464098,0.0003523332,0.0001973544,0.0004524989,0.03980419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04404706,"threshold_uncertainty_score":0.2329459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0252672075850435,"score_gpt":0.3088508037516696,"score_spread":0.283583596166626,"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."}}