{"id":"W2230402600","doi":"10.1080/15592324.2015.1058461","title":"Adjustments of lipid pathways in plant adaptation to temperature stress","year":2016,"lang":"en","type":"article","venue":"Plant Signaling & Behavior","topic":"Lipid metabolism and biosynthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Saskatchewan Research Council (Canada); University of Saskatchewan","funders":"National Research Council Canada; Ege Üniversitesi","keywords":"Endoplasmic reticulum; Biology; Chloroplast; Transcriptome; Adaptation (eye); Lipid metabolism; Metabolic pathway; Metabolite; Biochemistry; Cell biology; Arabidopsis; Membrane lipids; Flux (metallurgy); Unfolded protein response; Botany; Membrane; Metabolism; Gene; Gene expression; Chemistry; Mutant","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001305569,0.0001448413,0.0001755825,0.00007960331,0.0000289627,0.000009137033,0.0001561338,0.0001424964,0.00003314147],"category_scores_gemma":[0.00003614139,0.00009892185,0.00005124251,0.00006725462,0.00001812501,0.00000547594,0.00004889737,0.00004449987,0.000008768143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001151343,"about_ca_system_score_gemma":0.00005313521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002809416,"about_ca_topic_score_gemma":0.00005791607,"domain_scores_codex":[0.9990392,0.00004574293,0.000259931,0.000282741,0.0001590776,0.0002132694],"domain_scores_gemma":[0.9995791,0.00002215104,0.00008021715,0.0001950951,0.00004111937,0.0000822967],"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":[0.0001322157,0.0001601644,0.01017332,0.00001168479,0.00001041803,0.000008321216,0.0001456989,0.00001151439,0.9828522,0.0000149984,0.0001133976,0.00636603],"study_design_scores_gemma":[0.0004200281,0.00009872672,0.02490643,0.0001519257,0.00002734369,0.00000355333,0.0000889039,0.000001326118,0.9714803,8.975132e-7,0.002661406,0.0001592288],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978878,0.0001560735,0.00003595898,0.00002483172,0.0002425709,0.0002137229,0.001405481,0.000009450198,0.00002412035],"genre_scores_gemma":[0.9986688,0.00004809075,0.0004780079,0.0000556852,0.0002564009,0.00005404755,0.0003074288,0.00001525312,0.0001162496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01473311,"threshold_uncertainty_score":0.4033916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881241761394321,"score_gpt":0.228208974118723,"score_spread":0.2093965565047798,"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."}}