{"id":"W3202982215","doi":"10.1007/978-1-0716-1740-3_1","title":"Quantitative Genetic Screens for Mapping Bacterial Pathways and Functional Networks","year":2021,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina; University of Saskatchewan","funders":"Canadian Institutes of Health Research","keywords":"Mutant; Pairwise comparison; Biology; Computational biology; Gene; Genetics; Genetic screen; Genetic Fitness; Strain (injury); Replica; Gene mapping; Computer science; Artificial intelligence; Chromosome; Geography","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":[0.0006287028,0.001459785,0.0005723374,0.001742065,0.0004771545,0.0006958735,0.001058994,0.0005697064,0.002442936],"category_scores_gemma":[0.000949152,0.0006227104,0.0007459369,0.001077193,0.000818449,0.0003431793,0.0009229779,0.001431716,0.0003640207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001202995,"about_ca_system_score_gemma":0.0006297406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001671139,"about_ca_topic_score_gemma":0.003590703,"domain_scores_codex":[0.9992199,0.0001598322,0.00005085975,0.0001385851,0.0003348463,0.00009599372],"domain_scores_gemma":[0.998938,0.0006234009,0.0001781501,0.0001043947,0.00004995435,0.0001061522],"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":[0.00009554115,0.00006410562,0.0002705901,0.00007098458,0.00002483859,0.00006456369,0.00001079615,0.0009396672,0.9944615,0.001240212,0.00007951769,0.002677689],"study_design_scores_gemma":[0.000106522,0.000250031,0.003890866,0.00001424155,0.00009327078,0.0003141321,0.00004170862,0.01277219,0.9784712,0.001923102,0.002094967,0.0000277138],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8136036,0.001306265,0.1719944,0.0004331695,0.00007685417,0.0003822095,0.005554666,0.002045173,0.004603546],"genre_scores_gemma":[0.91413,0.001008188,0.07763607,0.0002349625,0.00001860897,0.0003836625,0.002656668,0.0003211627,0.003610611],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002442936,"threshold_uncertainty_score":0.008728445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03730979353986242,"score_gpt":0.3380916449980746,"score_spread":0.3007818514582122,"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."}}