{"id":"W4233004170","doi":"10.7287/peerj.preprints.27295","title":"QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":190,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Dalhousie University","funders":"","keywords":"Microbiome; Visualization; Scalability; Computer science; Data science; Metagenomics; Modular design; Data visualization; Computational biology; Biology; Bioinformatics; Data mining; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02077847,0.001696347,0.001352564,0.003666125,0.001597558,0.005498046,0.004708797,0.001585342,0.006120034],"category_scores_gemma":[0.05597069,0.002001571,0.002521296,0.003660575,0.001760827,0.006339294,0.01265943,0.005118991,0.004964477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181594,"about_ca_system_score_gemma":0.008649602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004812148,"about_ca_topic_score_gemma":0.00717375,"domain_scores_codex":[0.9869465,0.003097135,0.001594805,0.002067852,0.005321803,0.000971919],"domain_scores_gemma":[0.9740071,0.008189132,0.002101372,0.009096548,0.004390817,0.002215048],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002923692,0.0004957631,0.02757176,0.003101118,0.001072326,0.001229832,0.002807457,0.03220577,0.08158667,0.07469131,0.3822801,0.3900342],"study_design_scores_gemma":[0.0007498026,0.0003668272,0.008055627,0.0006230028,0.0002149332,0.001074788,0.0004071733,0.2359364,0.1134478,0.1664321,0.4718679,0.0008236577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.008809323,0.0007093472,0.8220412,0.002472125,0.0008102421,0.0008343221,0.03155653,0.1292601,0.003506796],"genre_scores_gemma":[0.04140516,0.000720971,0.8797478,0.001219575,0.0003069179,0.001579834,0.05989743,0.01267084,0.002451588],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.9792215,"threshold_uncertainty_score":0.1098884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3019415862077793,"score_gpt":0.4600509792033943,"score_spread":0.158109392995615,"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."}}