{"id":"W3204378948","doi":"10.3390/land10101058","title":"Elucidating Traditional Rice Varieties for Consilient Biotic and Abiotic Stress Management under Changing Climate with Landscape-Level Rice Biodiversity","year":2021,"lang":"en","type":"article","venue":"Land","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"King Saud University; Ministry of Agriculture and Farmers Welfare; Indian Council of Agricultural Research","keywords":"Biodiversity; Agriculture; Psychological resilience; Agroforestry; Geography; Environmental resource management; Climate change; Sustainability; Business; Ecology; Environmental 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001165413,0.000140412,0.0001480682,0.00001648088,0.0004164262,0.0001463736,0.00007463297,0.00005872188,0.00009660015],"category_scores_gemma":[0.00001112179,0.00005415049,0.00003567697,0.0002563809,0.0000426739,0.00009907547,0.00009824525,0.00006369327,0.000005545425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002170994,"about_ca_system_score_gemma":0.000003589201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004193529,"about_ca_topic_score_gemma":0.0007940653,"domain_scores_codex":[0.9990589,0.00002661167,0.000100219,0.0002873369,0.0001633696,0.0003635517],"domain_scores_gemma":[0.9995313,0.0001965275,0.00006667565,0.00004025013,0.00007338886,0.00009191447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007206636,0.001742573,0.8545373,0.002955403,0.0009720565,0.0004412663,0.005074228,0.0002546368,0.1066266,0.00845423,0.006358377,0.01186264],"study_design_scores_gemma":[0.0007200449,0.0001714188,0.9868131,0.00009304006,0.0001115187,0.0000664621,0.009499154,0.0001280315,0.001520872,0.0002508258,0.0003362022,0.0002893549],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951495,0.0001998634,0.00005551483,0.0025028,0.00007069766,0.0002370334,0.001359808,0.00004581,0.0003789542],"genre_scores_gemma":[0.9977703,0.0001833657,0.0003821084,0.0005660482,0.0001051109,0.000008319967,0.0008657651,0.000001006402,0.0001179429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1322758,"threshold_uncertainty_score":0.3202856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05598133490848169,"score_gpt":0.2138010442222017,"score_spread":0.15781970931372,"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."}}