{"id":"W4401700799","doi":"10.7554/elife.99352","title":"Systems genomics of salinity stress response in rice","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Plant Stress Responses and Tolerance","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Canada Research Chairs; University of California, Riverside; Heinrich-Heine-Universität Düsseldorf; York University; National Science Foundation; Zegar Family Foundation; Life Sciences Research Foundation; Gordon and Betty Moore Foundation; Fordham University","keywords":"Genomics; Fight-or-flight response; Biology; Salinity; Computational biology; Stress (linguistics); Genetics; Biotechnology; Evolutionary biology; Genome; Ecology; Gene","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":[0.0005088159,0.0002980425,0.000525531,0.0008154759,0.0003523331,0.0005762186,0.0002526295,0.0002118442,0.00137495],"category_scores_gemma":[0.0004920241,0.0001916481,0.00070883,0.001281609,0.0003194009,0.0003599874,0.0006344247,0.0005219752,0.0003251946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007994484,"about_ca_system_score_gemma":0.0007574485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004177546,"about_ca_topic_score_gemma":0.008476386,"domain_scores_codex":[0.9997373,0.00004288991,0.00001183437,0.0001483001,0.00003069167,0.00002893424],"domain_scores_gemma":[0.9998189,0.0000647885,0.00004218418,0.0000291999,0.00002288425,0.00002208206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004437417,0.00009756553,0.1063908,0.001275143,0.0007296231,0.0003627487,0.00175195,0.01471896,0.7860784,0.01089949,0.002242665,0.07500891],"study_design_scores_gemma":[0.00005490939,0.0002413581,0.9171956,0.00009389093,0.0003435639,0.0003567865,0.0007471855,0.01450048,0.01777031,0.02280606,0.02582196,0.00006799851],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9305061,0.002071927,0.03136945,0.0004844686,0.00002106668,0.00005637386,0.02905508,0.000544203,0.00589144],"genre_scores_gemma":[0.9336019,0.0014467,0.02578054,0.0003362146,0.00002400128,0.0001369459,0.03687743,0.0001958628,0.001600378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004177546,"threshold_uncertainty_score":0.008306444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02270452474729574,"score_gpt":0.2416709550636612,"score_spread":0.2189664303163655,"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."}}