{"id":"W4415570637","doi":"10.1007/s44154-025-00268-z","title":"Temporal proteomic profiling via 4D-DIA reveals early defense mechanisms and core resistance determinants in soybean against Phakopsora pachyrhizi","year":2025,"lang":"en","type":"article","venue":"Stress Biology","topic":"Yeasts and Rust Fungi Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"Key Laboratory of Agricultural Information Service Technology; Agricultural Science and Technology Innovation Program; National Key Research and Development Program of China; Chinese Academy of Agricultural Sciences","keywords":"Phakopsora pachyrhizi; Soybean rust; Proteomics; Plant disease resistance; Rust (programming language); Plant defense against herbivory; Signal transduction; Phenylpropanoid","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":[0.0001921079,0.0002374373,0.0003252241,0.00009114008,0.000148289,0.00002148156,0.0001715388,0.000274226,0.000002292225],"category_scores_gemma":[0.00008786147,0.0002008712,0.00005699871,0.0001121226,0.0002264417,0.000004186298,0.0002152413,0.0001431458,0.000002175749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002100424,"about_ca_system_score_gemma":0.00006707455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005433975,"about_ca_topic_score_gemma":0.0008409634,"domain_scores_codex":[0.9985923,0.0001016909,0.0002898901,0.0005636084,0.00004862127,0.0004039202],"domain_scores_gemma":[0.9994544,0.0000197524,0.0001204234,0.0002892448,0.00006114764,0.00005501905],"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":[0.0002423723,0.00004468971,0.3737129,0.00009791738,0.00006046794,0.00002138013,0.0000632646,0.000001154992,0.6217201,0.001797938,0.0001148127,0.002122961],"study_design_scores_gemma":[0.003183347,0.0007912078,0.06773309,0.0005663967,0.00007555252,0.00001096076,0.0004074697,0.00009320879,0.9113415,0.01221144,0.002516281,0.001069487],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942979,0.003537078,0.0006356193,0.0001300888,0.0001816907,0.0005295133,0.0001166463,0.00001686228,0.0005546438],"genre_scores_gemma":[0.9964602,0.0003888931,0.001793774,0.0001583719,0.00007027408,0.00009682321,0.00009164205,0.00001762525,0.0009223816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3059798,"threshold_uncertainty_score":0.8191289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01028037861645282,"score_gpt":0.2644263010375743,"score_spread":0.2541459224211214,"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."}}