{"id":"W2807006987","doi":"10.1373/clinchem.2018.286518","title":"Improving Equivalency in Metagenomics: A Harmonized Process to Extract Fecal DNA","year":2018,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services; University of Calgary","funders":"","keywords":"Harmonization; Metagenomics; Computational biology; Fecal bacteriotherapy; Biology; Medicine; Genetics; Clostridium difficile; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006659678,0.0001924144,0.0002997633,0.00001914142,0.00006439639,0.0000271518,0.0003703549,0.0003720436,0.0001704637],"category_scores_gemma":[0.0006886345,0.0001907976,0.0001437552,0.0001146796,0.0001519488,0.000004118563,0.0001877047,0.0002829521,0.00008575169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002992138,"about_ca_system_score_gemma":0.00030682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009458651,"about_ca_topic_score_gemma":0.00001919434,"domain_scores_codex":[0.998102,0.00004636297,0.0006348735,0.0006804923,0.00008686807,0.0004493873],"domain_scores_gemma":[0.9989705,0.00003336488,0.0001328357,0.0004666975,0.0001103379,0.0002862474],"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":[0.0002370229,0.0001774246,0.008721982,0.0001087059,0.00001769236,0.000006350006,0.00003320193,5.133877e-7,0.9854552,0.000001223045,0.001013535,0.004227221],"study_design_scores_gemma":[0.001635392,0.0003806711,0.006755004,0.00004932405,0.00002503956,0.00002078962,0.00008196011,0.00006412182,0.9650159,0.00004725879,0.02551045,0.0004140864],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970317,0.0002607741,0.0002647958,0.0003148544,0.0001749051,0.0002054574,0.00001730557,0.00001949807,0.00171073],"genre_scores_gemma":[0.9950919,0.00004959288,0.001164094,0.001198929,0.001201496,0.0000233956,0.00004682366,0.00003128691,0.001192516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02449692,"threshold_uncertainty_score":0.77805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04290672321599241,"score_gpt":0.3932661332943642,"score_spread":0.3503594100783718,"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."}}