{"id":"W4319915600","doi":"10.1038/s41467-023-36129-4","title":"Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"Plant responses to water stress","field":"Agricultural and Biological Sciences","cited_by":229,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Grains Research and Development Corporation","keywords":"Waterlogging (archaeology); Temperate climate; Climate change; Food security; Environmental science; Crop; Evapotranspiration; Sowing; Yield (engineering); Frost (temperature); Agronomy; Crop yield; Cropping; Growing season; Agriculture; Geography; Biology; Ecology; Meteorology; Wetland","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":[0.001355097,0.0004429376,0.000393176,0.0002905512,0.0006677866,0.002703914,0.0007238083,0.001481383,0.004373769],"category_scores_gemma":[0.00171628,0.0002917486,0.000573342,0.0004468709,0.001650749,0.003019163,0.0021295,0.00144456,0.0004220231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517917,"about_ca_system_score_gemma":0.001328403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00485547,"about_ca_topic_score_gemma":0.008553303,"domain_scores_codex":[0.9996458,0.0001338729,0.00001043557,0.00009416316,0.00004026811,0.00007532621],"domain_scores_gemma":[0.9994366,0.0001031378,0.0001724656,0.00008031294,0.00005920775,0.0001482199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007878889,0.0003100521,0.1393533,0.0009819603,0.0004277336,0.001684021,0.003755171,0.3127896,0.08489548,0.2871126,0.0189054,0.1489968],"study_design_scores_gemma":[0.00005101141,0.0004068495,0.1232352,0.0002998442,0.0001485419,0.0003761071,0.008050023,0.276158,0.006722727,0.5195392,0.06483117,0.000181146],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7710539,0.002769132,0.1404884,0.03269526,0.0005384103,0.00007940303,0.0009332963,0.0006144621,0.05082778],"genre_scores_gemma":[0.990121,0.0007264664,0.006962907,0.0005675122,0.00003885965,0.00002915954,0.0001097164,0.0000452362,0.0013993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00485547,"threshold_uncertainty_score":0.01463169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04434510321966969,"score_gpt":0.3027733639489573,"score_spread":0.2584282607292876,"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."}}