{"id":"W4379508482","doi":"10.1007/s11248-023-00354-w","title":"GEnZ explorer: a tool for visualizing agroclimate to inform research and regulatory risk assessment","year":2023,"lang":"en","type":"article","venue":"Transgenic Research","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University","funders":"Foreign Agricultural Service","keywords":"Transparency (behavior); Risk assessment; Biology; Visualization; Data science; Risk analysis (engineering); Computer science; Business; Data mining","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":[0.005332611,0.002124535,0.001187293,0.006627757,0.0008777668,0.00366275,0.002198339,0.001759419,0.05320607],"category_scores_gemma":[0.0177417,0.0007978932,0.002025524,0.00425026,0.0007231451,0.004159241,0.005416211,0.001920904,0.01304417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000976642,"about_ca_system_score_gemma":0.002955607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006232803,"about_ca_topic_score_gemma":0.0112984,"domain_scores_codex":[0.9979714,0.0006689791,0.0002309427,0.0003367298,0.0006381404,0.0001538805],"domain_scores_gemma":[0.9876229,0.00828641,0.0009667108,0.001372396,0.001214411,0.0005371739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001572191,0.0002166062,0.01236809,0.007341313,0.0005004617,0.001318603,0.004363284,0.008728579,0.0111156,0.02436652,0.6647063,0.2634025],"study_design_scores_gemma":[0.0003634412,0.0001374418,0.01159819,0.001327807,0.0001905365,0.0006665392,0.001156187,0.01510157,0.009693799,0.03755623,0.9218401,0.0003681342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01444952,0.003049528,0.2841332,0.003167381,0.0009150704,0.001001967,0.2690474,0.3832122,0.04102378],"genre_scores_gemma":[0.1242493,0.004700906,0.598537,0.002727638,0.0003331072,0.004318935,0.1714692,0.07189173,0.02177222],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.05320607,"threshold_uncertainty_score":0.177992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3244624424621861,"score_gpt":0.4701047490184415,"score_spread":0.1456423065562554,"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."}}