{"id":"W4407731062","doi":"10.1038/s43016-025-01143-w","title":"Author Correction: Governance and resilience as entry points for transforming food systems in the countdown to 2030","year":2025,"lang":"en","type":"erratum","venue":"Nature Food","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Countdown; Resilience (materials science); Corporate governance; Business; Environmental resource management; Environmental planning; Political science; Environmental science; Engineering; Finance; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004462987,0.0004072553,0.0004487522,0.00002387959,0.0003461807,0.0002028378,0.0006821033,0.001204932,0.00001475998],"category_scores_gemma":[0.0002916981,0.0001296698,0.0001232103,0.0007549661,0.00003038279,0.0001213222,0.00007369757,0.001389777,0.000005938351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001623402,"about_ca_system_score_gemma":0.00006933406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001368276,"about_ca_topic_score_gemma":0.005399515,"domain_scores_codex":[0.9977075,0.0000923409,0.0003937547,0.0006942351,0.0006251594,0.0004869577],"domain_scores_gemma":[0.9990951,0.0003586456,0.0001762961,0.000107044,0.0001579501,0.0001049025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008273401,0.00004244737,0.00009093635,0.000120315,0.00003366762,0.000003978801,0.0003131036,0.000002529145,0.0000288494,0.002987059,0.9863425,0.009951881],"study_design_scores_gemma":[0.0001907101,0.0008406202,0.02241186,0.0008711847,0.000032725,0.00003957067,0.0009045939,0.00001057022,0.00009357421,0.0008575465,0.9733585,0.0003885425],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3917483,0.1494123,0.00005659202,0.1067004,0.238786,0.02491952,0.0077898,0.0006620507,0.07992508],"genre_scores_gemma":[0.7237226,0.001755935,0.0001025929,0.006858835,0.005220436,0.001313851,0.001259055,0.000009010308,0.2597577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3319743,"threshold_uncertainty_score":0.9293542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009063498774908795,"score_gpt":0.2320831627592555,"score_spread":0.2230196639843467,"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."}}