{"id":"W6939339824","doi":"10.6084/m9.figshare.26600311","title":"Additional file 8 of MetaPro: a scalable and reproducible data processing and analysis pipeline for metatranscriptomic investigation of microbial communities","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Pipeline (software); Table (database); Weissella; Scalability; Annotation; Leuconostoc; Lactobacillus","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002283052,0.002703608,0.001787944,0.00267528,0.001308124,0.002714081,0.003683743,0.002221771,0.3238493],"category_scores_gemma":[0.008638867,0.001035127,0.00179355,0.004055513,0.0006117323,0.002052749,0.002211948,0.002162694,0.1342504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001397181,"about_ca_system_score_gemma":0.002611442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008552522,"about_ca_topic_score_gemma":0.0197645,"domain_scores_codex":[0.9987364,0.0001597087,0.0001616482,0.000476547,0.0002687251,0.0001969118],"domain_scores_gemma":[0.9968734,0.00139765,0.0002979658,0.0005410687,0.0006047382,0.0002851391],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003462985,0.000104742,0.00379917,0.003072966,0.0001434614,0.00007788778,0.00007868709,0.0008356526,0.001131373,0.0006634831,0.9848776,0.004868734],"study_design_scores_gemma":[0.001988207,0.0001537957,0.01550031,0.001033723,0.0001874308,0.0002115567,0.0002032017,0.00217078,0.003654418,0.004568363,0.9701756,0.000152683],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.00009449468,0.00001270458,0.0001644907,0.00002011225,0.0000113116,0.00001996697,0.9989371,0.0005669629,0.000172927],"genre_scores_gemma":[0.0006285,0.00002193286,0.001239223,0.00005911405,0.000007643972,0.0002096267,0.9970235,0.0003279693,0.0004824802],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.997717,"threshold_uncertainty_score":0.9644469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06499599340391936,"score_gpt":0.2542135685261895,"score_spread":0.1892175751222702,"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."}}