{"id":"W2138527737","doi":"10.1186/s13104-015-1170-4","title":"Optimizing a PCR protocol for cpn60-based microbiome profiling of samples variously contaminated with host genomic DNA","year":2015,"lang":"en","type":"article","venue":"BMC Research Notes","topic":"Yersinia bacterium, plague, ectoparasites research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pyrosequencing; Microbiome; Biology; Computational biology; genomic DNA; Polymerase chain reaction; Genetics; DNA; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001833666,0.0002394211,0.0003242599,0.0003179376,0.0001581389,0.0001097519,0.0005540153,0.0002102228,0.0000155512],"category_scores_gemma":[0.001724753,0.0002024451,0.00009915841,0.0003920425,0.0004559055,0.00001287273,0.0002460913,0.0002419418,0.000009323273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001160418,"about_ca_system_score_gemma":0.001929038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000237764,"about_ca_topic_score_gemma":0.0003431597,"domain_scores_codex":[0.9972646,0.000398331,0.0003582546,0.0006306883,0.0004924547,0.0008557317],"domain_scores_gemma":[0.9970183,0.0004765799,0.0001333502,0.0006138917,0.001492803,0.0002650578],"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":[0.004336656,0.0001994219,0.02234912,0.0004636974,0.00005752845,0.000005561456,0.00009551747,0.0002401177,0.9718606,0.00001817537,0.0002675616,0.0001059853],"study_design_scores_gemma":[0.004617747,0.00286375,0.00343525,0.0001174467,0.000009081516,0.00001285484,0.0001345039,0.00107774,0.9841235,0.00001671269,0.003333631,0.0002577477],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9196958,0.00004287009,0.01168247,0.0001074486,0.0000207637,0.06804495,0.000226138,0.00002591894,0.0001536221],"genre_scores_gemma":[0.8395556,0.000001731936,0.09132248,0.00002604485,0.0001525829,0.06818539,0.0004838152,0.00009597974,0.0001763883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08014023,"threshold_uncertainty_score":0.8255472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1893978647776628,"score_gpt":0.4163110276064556,"score_spread":0.2269131628287927,"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."}}