{"id":"W3159940416","doi":"10.1111/cmi.13349","title":"<scp>HRMAn</scp> 2.0: Next‐generation artificial intelligence–driven analysis for broad host–pathogen interactions","year":2021,"lang":"en","type":"article","venue":"Cellular Microbiology","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Boehringer Ingelheim Fonds; Wellcome Trust; Francis Crick Institute; Medical Research Council Canada; Cancer Research UK","keywords":"Biology; Host (biology); Pathogen; Computational biology; Virology; Microbiology; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002286302,0.001360464,0.0008542056,0.00132,0.0005327424,0.001591536,0.00318517,0.001326478,0.06362189],"category_scores_gemma":[0.003407588,0.0006951781,0.001021377,0.001021316,0.0007622826,0.001516368,0.001642072,0.002383914,0.02521613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000962334,"about_ca_system_score_gemma":0.0009568722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002647966,"about_ca_topic_score_gemma":0.00458121,"domain_scores_codex":[0.9989951,0.0001112802,0.00005230524,0.0001821038,0.0005913064,0.00006789554],"domain_scores_gemma":[0.9980563,0.0007179315,0.0001785721,0.0003972557,0.0004968984,0.0001530823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004651358,0.0001170387,0.001621597,0.0007357033,0.0002134299,0.000515245,0.0001612038,0.00968821,0.05136476,0.01637302,0.7913809,0.1273637],"study_design_scores_gemma":[0.0002392413,0.0001684545,0.004126261,0.000144996,0.00007815428,0.0005862989,0.00004029289,0.3487849,0.1286836,0.03202619,0.4848224,0.0002992379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005542183,0.0004463056,0.547265,0.001534506,0.0007969084,0.0002824957,0.02958461,0.3930167,0.02153126],"genre_scores_gemma":[0.07043388,0.001034911,0.7369004,0.002885081,0.0004400835,0.001796283,0.06390339,0.09214101,0.03046498],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06362189,"threshold_uncertainty_score":0.2128364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05817425028167467,"score_gpt":0.2848322639496605,"score_spread":0.2266580136679859,"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."}}