{"id":"W3096696810","doi":"10.1101/2020.10.30.363010","title":"Differential alteration of plant functions by homologous fungal candidate effectors","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Plant-Microbe Interactions and Immunity","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service; Natural Resources Canada; Université du Québec à Trois-Rivières","funders":"Fonds de recherche du Québec – Nature et technologies; Fondation de l’UQTR; Natural Sciences and Engineering Research Council of Canada; Mitacs; Université du Québec à Trois-Rivières","keywords":"Arabidopsis; Biology; Transcriptome; Effector; Gene; KEGG; Metabolome; Genetically modified crops; Rust (programming language); Transgene; Metabolomics; Plant defense against herbivory; Genetics; Metabolite; RNA-Seq; Arabidopsis thaliana; Gene expression; Cell biology; Biochemistry; Mutant; Bioinformatics","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":[0.0000970544,0.0003281535,0.0001988131,0.0002772054,0.00009466,0.0002233638,0.00009012969,0.0001830427,0.0007510086],"category_scores_gemma":[0.00009945167,0.0001102625,0.0002273477,0.0001933831,0.0001008698,0.0001329937,0.0001447903,0.0002727703,0.0001825799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001636662,"about_ca_system_score_gemma":0.00006482589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002029303,"about_ca_topic_score_gemma":0.0002452892,"domain_scores_codex":[0.9998863,0.00001198494,0.000008508495,0.00003669231,0.00003166805,0.0000248172],"domain_scores_gemma":[0.9998664,0.00003032662,0.00004511558,0.0000126696,0.00002358747,0.00002188202],"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":[0.00002230126,0.000004758366,0.0005138976,0.000007148367,0.000002783899,0.00001335762,0.000002994574,0.0000130589,0.999154,0.000006241252,0.000003680555,0.0002558817],"study_design_scores_gemma":[0.000007599943,0.0001989285,0.1076543,0.000005710979,0.00003847002,0.0004214586,0.00005567998,0.001007188,0.8895805,0.00005672914,0.0009672025,0.00000606841],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979503,0.0003692526,0.0008944393,0.00001844758,0.000004685081,0.000005038399,0.0005017025,0.0000323229,0.0002238687],"genre_scores_gemma":[0.9964997,0.0001884832,0.00109483,0.00002934904,0.000003147836,0.000009932086,0.001302851,0.00001303458,0.0008587856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007510086,"threshold_uncertainty_score":0.002512395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181604934689868,"score_gpt":0.1924558558210034,"score_spread":0.1806398064741047,"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."}}