{"id":"W4409148367","doi":"10.1016/j.tplants.2025.03.003","title":"The plant proteome delivers from discovery to innovation","year":2025,"lang":"en","type":"review","venue":"Trends in Plant Science","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Mitacs; Grain Farmers of Ontario; Ontario Ministry of Agriculture, Food and Rural Affairs; Canada Foundation for Innovation","keywords":"Proteomics; Leverage (statistics); Data science; Biology; Proteome; Biotechnology; Scientific discovery; Plant science; Plant disease; Computational biology; Computer science; Bioinformatics; Artificial intelligence; Cognitive science","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":[0.000317782,0.000245488,0.0004233758,0.0004861798,0.0003171924,0.0001688856,0.001351169,0.0001255919,0.00002083693],"category_scores_gemma":[0.0001117706,0.0001655192,0.00006722938,0.003176347,0.0001844362,0.0001719536,0.0003331364,0.0004041161,0.00001046139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003275487,"about_ca_system_score_gemma":0.0003450738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008274198,"about_ca_topic_score_gemma":0.0000450131,"domain_scores_codex":[0.9982404,0.00001120551,0.000510906,0.0006068603,0.0002936382,0.0003370046],"domain_scores_gemma":[0.998749,0.000248657,0.0002563378,0.0006673155,0.00003558385,0.00004311666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006872802,0.00001891443,0.000004258341,0.0004041288,0.00000643696,0.000004614754,0.00002369563,0.000006628406,0.0004156163,0.01211622,0.0006065142,0.9863861],"study_design_scores_gemma":[0.00004378127,0.000005984333,0.000002906675,0.005246886,0.00002532087,0.000005257137,0.0000128913,0.00003343875,0.001630741,0.001207176,0.9915254,0.0002602033],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003277526,0.9525116,0.006865038,0.0003482675,0.0003366202,0.001543898,0.01394216,0.0003381999,0.02378647],"genre_scores_gemma":[0.00004506087,0.9882569,0.005927567,0.00003847619,0.00006443791,0.001167063,0.0009306627,0.00001398109,0.003555863],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9909189,"threshold_uncertainty_score":0.6749676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0468016944504165,"score_gpt":0.3540281399696735,"score_spread":0.307226445519257,"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."}}