{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001221353,0.001515604,0.001881998,0.002247417,0.0003461259,0.002467389,0.001078033,0.00188257,0.005402168],"category_scores_gemma":[0.001324895,0.0004071417,0.0005183998,0.002703795,0.001060785,0.004275088,0.001838316,0.003746458,0.00437783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001259006,"about_ca_system_score_gemma":0.001778077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000743417,"about_ca_topic_score_gemma":0.00150608,"domain_scores_codex":[0.9996653,0.00005173104,0.00002566569,0.00005270307,0.0001598257,0.00004492452],"domain_scores_gemma":[0.9994005,0.0002692676,0.00006440145,0.00002549639,0.0001473532,0.00009293731],"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":[0.00007821368,0.00004093219,0.00007038932,0.01069949,0.00007101287,0.00009920305,0.00003457127,0.0002891918,0.00392366,0.01262858,0.05277501,0.9192897],"study_design_scores_gemma":[0.00001202515,0.00003549423,0.0001791776,0.001323471,0.00004292468,0.000191859,0.00002256977,0.00007113407,0.0005687627,0.004304681,0.9932359,0.00001192658],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006205924,0.9962913,0.0003409088,0.0007599392,0.0008480977,0.000003759709,0.00002058486,0.00001869811,0.001654643],"genre_scores_gemma":[0.000436055,0.9970745,0.0002726371,0.0005345622,0.0005756964,0.000005460159,0.00003372857,0.000003459928,0.001063981],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005402168,"threshold_uncertainty_score":0.01807207,"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."}}