{"id":"W2754117488","doi":"10.5006/c2017-09420","title":"Molecular MIC Diagnoses from ATP Field Test: Streamlined Workflow from Field to 16S rRNA Gene Metagenomics Results","year":2017,"lang":"en","type":"article","venue":"","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Metagenomics; Workflow; 16S ribosomal RNA; Computational biology; Ribosomal RNA; Biology; Gene; Computer science; Genetics; Database","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005304377,0.002469478,0.002372204,0.005024014,0.0009381469,0.00315628,0.002136611,0.001601195,0.00545216],"category_scores_gemma":[0.0100341,0.001302195,0.001638787,0.001604644,0.0007577928,0.001611993,0.003819259,0.00242437,0.0109959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008914397,"about_ca_system_score_gemma":0.002262015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001966314,"about_ca_topic_score_gemma":0.002638345,"domain_scores_codex":[0.9921531,0.001543797,0.001005759,0.001404521,0.003474252,0.0004184273],"domain_scores_gemma":[0.9901767,0.001883921,0.001361812,0.001688924,0.004082467,0.0008060876],"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":[0.000879616,0.0004533574,0.02462173,0.001123344,0.0002083891,0.001602387,0.0008335442,0.003163683,0.7508137,0.001463766,0.01692965,0.1979069],"study_design_scores_gemma":[0.00008493967,0.0007675443,0.03443575,0.0005195998,0.0002111395,0.00151077,0.001081893,0.05228946,0.8353873,0.005575511,0.06767135,0.0004647626],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06933505,0.001314593,0.8551674,0.002675598,0.001174493,0.00348854,0.01069402,0.04854427,0.007606102],"genre_scores_gemma":[0.1364436,0.001077107,0.844799,0.001228552,0.0003722912,0.001902255,0.007020554,0.003049792,0.004106856],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00545216,"threshold_uncertainty_score":0.02805257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01077402846297008,"score_gpt":0.2798366242281769,"score_spread":0.2690625957652068,"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."}}