{"id":"W4226243051","doi":"10.3389/fnut.2022.856491","title":"Gene-Edited Meat: Disentangling Consumers' Attitudes and Potential Purchase Behavior","year":2022,"lang":"en","type":"article","venue":"Frontiers in Nutrition","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Biotechnology and Biological Sciences Research Council","keywords":"Livestock; Sustainability; Consumption (sociology); Business; Marketing; Production (economics); Food security; Animal welfare; Quality (philosophy); Agriculture; Food processing; Biotechnology; Economics; Food science; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00124069,0.0001464262,0.0001646851,0.0002362259,0.0003196223,0.001035778,0.00009485554,0.0003796215,0.003264241],"category_scores_gemma":[0.003015309,0.000113515,0.0002879144,0.0001745225,0.0003924486,0.0006024523,0.0003943334,0.0007693201,0.0003060936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001948964,"about_ca_system_score_gemma":0.0001754895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002832471,"about_ca_topic_score_gemma":0.004059079,"domain_scores_codex":[0.9996234,0.0001650274,0.00001599365,0.00005890402,0.00008240983,0.00005422902],"domain_scores_gemma":[0.9982743,0.0008389661,0.0004071088,0.0001074314,0.0001722361,0.0001999544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007872539,0.0008430993,0.963825,0.00006438779,0.0001498198,0.0001295369,0.01118757,0.00007501445,0.004335422,0.0005358437,0.0003638217,0.01770307],"study_design_scores_gemma":[0.00001139958,0.0003764309,0.9881132,0.00002462612,0.00007439019,0.00009971477,0.008021173,0.0008364189,0.0006159553,0.0006407642,0.001165623,0.00002028999],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985536,0.00003996425,0.0001984406,0.0001016286,0.000004275915,0.000005565723,0.00003562027,0.000001670026,0.001059358],"genre_scores_gemma":[0.9991335,0.00003466618,0.0001692838,0.00008730077,0.000003809731,0.0000078579,0.00003753094,0.000001677677,0.0005244559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003264241,"threshold_uncertainty_score":0.01091999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004939467858404848,"score_gpt":0.2601554022859268,"score_spread":0.255215934427522,"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."}}