{"id":"W3040192468","doi":"10.1016/j.xpro.2020.100057","title":"High-Throughput Chemical Screening for Inhibitors of Salmonella Pathogenicity Island 2","year":2020,"lang":"en","type":"article","venue":"STAR Protocols","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research","keywords":"Virulence; Salmonella; High-throughput screening; Identification (biology); Biology; Pathogenicity island; Throughput; Computational biology; Protocol (science); Screening techniques; Pathogenicity; Microbiology; Genetics; Bacteria; Gene; Bioinformatics; Computer science; Medicine; Telecommunications","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":[0.0008579641,0.001123437,0.0009057684,0.0008676304,0.0003872057,0.0005176126,0.000719143,0.0005717196,0.002672511],"category_scores_gemma":[0.0003938511,0.0005181691,0.0005495748,0.0007601521,0.0002338779,0.0002938226,0.0005131872,0.0009456136,0.001845382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000418737,"about_ca_system_score_gemma":0.0006685893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006033735,"about_ca_topic_score_gemma":0.002902834,"domain_scores_codex":[0.9992486,0.0001221375,0.0000466467,0.00009896678,0.000399719,0.00008387116],"domain_scores_gemma":[0.9998069,0.0000558438,0.00002554088,0.00002755482,0.0000538075,0.0000304155],"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":[0.00009595384,0.0002363793,0.0001290906,0.0001549105,0.00002700902,0.0000386235,0.00001439628,0.0005635214,0.9912948,0.0001610608,0.00115186,0.006132373],"study_design_scores_gemma":[0.00006613908,0.0007936289,0.0008274105,0.00001064381,0.00003450529,0.0001190966,0.0000101969,0.001931563,0.9873859,0.00007625247,0.008727005,0.00001772954],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"protocol","genre_scores_codex":[0.6364444,0.01362819,0.2879401,0.001538121,0.0004476111,0.006347492,0.02453987,0.005386886,0.0237273],"genre_scores_gemma":[0.6592194,0.01788205,0.23019,0.0009268397,0.0001030765,0.006002289,0.04211698,0.0005525674,0.04300686],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.002672511,"threshold_uncertainty_score":0.008940458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06961064434213207,"score_gpt":0.2887117031223261,"score_spread":0.2191010587801941,"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."}}