{"id":"W2406163589","doi":"10.1038/srep26425","title":"The microbiomes and metagenomes of forest biochars","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; Laurentian University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Biochar; Acidobacteria; Microbial population biology; Abundance (ecology); Soil water; Biology; Metagenomics; Microbiome; Ecology; Proteobacteria; Chemistry; Bacteria","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002419789,0.0003175221,0.0002924674,0.001092991,0.0005402486,0.000676622,0.0001586341,0.0003112214,0.0003864045],"category_scores_gemma":[0.0004337528,0.0001853339,0.0002895954,0.0005680543,0.0002863617,0.0004945525,0.0004752781,0.0002159696,0.0001346832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002536101,"about_ca_system_score_gemma":0.0003017926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00421605,"about_ca_topic_score_gemma":0.007091259,"domain_scores_codex":[0.9997563,0.00002672511,0.00001635945,0.00009039885,0.0000532977,0.0000569432],"domain_scores_gemma":[0.9997665,0.00003630253,0.00006132023,0.00001781429,0.00006663952,0.00005132916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004726816,0.00006652003,0.1838322,0.0001304129,0.00009685265,0.00008956252,0.000417302,0.0004124869,0.8002665,0.0001204729,0.00005222641,0.01404278],"study_design_scores_gemma":[0.000005551912,0.0002374511,0.9658983,0.0000155128,0.00005835962,0.0002439774,0.0004522008,0.000725352,0.03129072,0.0001338879,0.0009276473,0.00001117347],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984046,0.0003867924,0.0005171268,0.00001166119,0.000003887987,0.000007738042,0.0003514462,0.000006849265,0.0003099508],"genre_scores_gemma":[0.9970644,0.000359163,0.001519568,0.0000247553,0.000006197537,0.00001397706,0.0006422604,0.000008300635,0.0003614214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00421605,"threshold_uncertainty_score":0.008383036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007417433483140035,"score_gpt":0.2051291743131137,"score_spread":0.1977117408299737,"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."}}