{"id":"W2041002927","doi":"10.1371/journal.pone.0034007","title":"Comparing the Similarity of Different Groups of Bacteria to the Human Proteome","year":2012,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Proteome; Biology; Human proteome project; Bacteria; Similarity (geometry); Proteomics; Computational biology; Microbiology; Bioinformatics; Genetics; Artificial intelligence; Gene; Computer science","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":[0.001059563,0.0002016628,0.0004197385,0.002141916,0.0003739626,0.0006463015,0.0002020643,0.0003608079,0.001732705],"category_scores_gemma":[0.002756575,0.00009487734,0.0003869957,0.001808049,0.0003796033,0.000579573,0.0006291734,0.0002570175,0.0004046813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001678813,"about_ca_system_score_gemma":0.0002373753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006267695,"about_ca_topic_score_gemma":0.0007351292,"domain_scores_codex":[0.999252,0.0002405428,0.00006501555,0.0002280121,0.0001361168,0.00007820631],"domain_scores_gemma":[0.9987403,0.0006195062,0.0002846907,0.0001164903,0.0001365936,0.0001025045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001601486,0.0001946853,0.6099753,0.0009958654,0.00101966,0.0009630964,0.001685291,0.002090044,0.2651533,0.001743229,0.001286422,0.1132916],"study_design_scores_gemma":[0.00002031987,0.0007029778,0.9430324,0.00006754643,0.0002338229,0.003806535,0.002007997,0.006270903,0.03338334,0.003386637,0.007043885,0.00004363546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895447,0.002529435,0.004943709,0.0001366219,0.0000196809,0.00001982088,0.0006361944,0.00004328206,0.002126473],"genre_scores_gemma":[0.9900456,0.001037857,0.007160913,0.00007934174,0.00001799187,0.00001359294,0.001325035,0.00001379055,0.0003059004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002141916,"threshold_uncertainty_score":0.005796492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04229954663577545,"score_gpt":0.2561524690765193,"score_spread":0.2138529224407439,"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."}}