{"id":"W4385863451","doi":"10.1371/journal.pone.0290070","title":"Social acceptance of genetic engineering technology","year":2023,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Government of Canada; Genome Canada; Ontario Genomics; University of British Columbia; University of Guelph; Ontario Genomics Institute","keywords":"Computer science; Data science","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":[0.01053351,0.0003139922,0.0003692857,0.0007544553,0.0009036086,0.002636558,0.0004170487,0.001126636,0.005374796],"category_scores_gemma":[0.03903026,0.0001776335,0.0006237577,0.000342064,0.001904478,0.001463835,0.001771407,0.001404453,0.0003467774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001179718,"about_ca_system_score_gemma":0.0008611086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002013349,"about_ca_topic_score_gemma":0.001635304,"domain_scores_codex":[0.9862462,0.009706516,0.0005146312,0.0005266417,0.002493217,0.000512824],"domain_scores_gemma":[0.9527841,0.02790454,0.009566422,0.00202358,0.005378406,0.00234303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007781344,0.001482884,0.6470555,0.001117643,0.0005170559,0.001232383,0.1694182,0.00145146,0.01040682,0.01274181,0.002587534,0.1512106],"study_design_scores_gemma":[0.0001517316,0.003108131,0.7889229,0.0007673695,0.000422824,0.001386304,0.1287015,0.009383493,0.004069241,0.01385439,0.04884862,0.0003834186],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876957,0.0002184342,0.002176472,0.001240137,0.00003363193,0.00006133342,0.0000399655,0.00001507301,0.008519256],"genre_scores_gemma":[0.9984381,0.0001362318,0.0005480087,0.0002234328,0.00002039203,0.00003822863,0.00002742658,0.00000534211,0.0005628889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01053351,"threshold_uncertainty_score":0.05570722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06679239605742684,"score_gpt":0.2373167611753945,"score_spread":0.1705243651179677,"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."}}