{"id":"W7164035735","doi":"10.5281/zenodo.20598578","title":"Investigating the Interactome of A. thaliana MPKs: An Integrative Approach Using Multiple Sources of Evidence and Machine Learning–Based Structural Modeling","year":2024,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Interactome; Systems biology; Construct (python library); Computational model","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0018786,0.001006641,0.001211301,0.003744672,0.001085504,0.002106491,0.0007496379,0.0009787556,0.003215068],"category_scores_gemma":[0.003481263,0.0006705841,0.002361728,0.002376266,0.0004783577,0.001859613,0.001323882,0.00142087,0.0008066269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007666138,"about_ca_system_score_gemma":0.001004537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00225129,"about_ca_topic_score_gemma":0.007913758,"domain_scores_codex":[0.9995176,0.0001296955,0.00002987315,0.0001944012,0.00009465524,0.00003378015],"domain_scores_gemma":[0.9975115,0.001658622,0.0002871327,0.0001990326,0.0002058133,0.0001377811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002782034,0.0004780311,0.09609207,0.008666763,0.009884135,0.002510651,0.00111312,0.07809074,0.5273768,0.01691415,0.009261459,0.24683],"study_design_scores_gemma":[0.0003394522,0.00078231,0.1444533,0.001156698,0.008313436,0.002746529,0.001457044,0.6556277,0.08652744,0.05790689,0.04034945,0.000339746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7351286,0.02146621,0.2135668,0.002782157,0.0001553518,0.0001726005,0.01754416,0.002230229,0.00695374],"genre_scores_gemma":[0.7941987,0.005939568,0.1805198,0.0004042808,0.00006711193,0.0001151397,0.0173211,0.0004305681,0.001003728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003744672,"threshold_uncertainty_score":0.01075548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1093708966057238,"score_gpt":0.3124236795659064,"score_spread":0.2030527829601826,"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."}}