{"id":"W3093731254","doi":"10.3791/61881","title":"Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions","year":2020,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Fungal Infections and Studies","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Proteome; Biology; Cryptococcus neoformans; Proteomics; Pathogen; Quantitative proteomics; Computational biology; Virulence; Host–pathogen interaction; Microbiology; Human pathogen; Intracellular parasite; Cell biology; Bacteria; Bioinformatics; Intracellular; Genetics; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003329171,0.001308269,0.001092233,0.001688109,0.0009287281,0.001933679,0.001748142,0.001148558,0.004766207],"category_scores_gemma":[0.001684699,0.0007797304,0.0007877928,0.001066089,0.0006101572,0.001029305,0.002165671,0.001985537,0.004839963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128301,"about_ca_system_score_gemma":0.002539066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008995029,"about_ca_topic_score_gemma":0.00105279,"domain_scores_codex":[0.997512,0.000278078,0.0002375761,0.0007644725,0.0009767616,0.0002310714],"domain_scores_gemma":[0.9988406,0.0002742026,0.0001252259,0.0002436116,0.0003991964,0.0001170387],"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":[0.0006026349,0.0001460939,0.001007977,0.0003891308,0.00005825464,0.0002468865,0.0001452018,0.001766347,0.9487042,0.002890787,0.004182294,0.03986017],"study_design_scores_gemma":[0.0001076947,0.0002555443,0.002110664,0.00008434981,0.00004721138,0.000446992,0.0000881473,0.04604638,0.9010043,0.005510496,0.04412534,0.0001727698],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02772474,0.0007499382,0.9387331,0.0004453452,0.0002243113,0.001119379,0.006496841,0.02109926,0.003407104],"genre_scores_gemma":[0.08128569,0.0007373255,0.9008363,0.0005446188,0.00008385145,0.003019052,0.00766673,0.001453075,0.004373259],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004766207,"threshold_uncertainty_score":0.01760656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09919735461018725,"score_gpt":0.471500171831813,"score_spread":0.3723028172216258,"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."}}