{"id":"W2066966261","doi":"10.1016/s0960-8524(01)00229-2","title":"Effect of carbon source on compost nitrogen and carbon losses","year":2002,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Composting and Vermicomposting Techniques","field":"Agricultural and Biological Sciences","cited_by":307,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Compost; Aeration; Straw; Volatilisation; Humidity; Chemistry; Nitrogen; Carbon dioxide; Animal science; Pulp and paper industry; Manure; Carbon fibers; Agronomy; Biology; Materials science","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":[0.0007666412,0.00122029,0.001049269,0.0007649398,0.0004916307,0.001358849,0.0009918379,0.001464515,0.003969512],"category_scores_gemma":[0.002676468,0.0004960177,0.0004414709,0.0008415467,0.0009653272,0.001257146,0.0005060136,0.001022846,0.0006562381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001381936,"about_ca_system_score_gemma":0.00116092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005836302,"about_ca_topic_score_gemma":0.009113994,"domain_scores_codex":[0.9990829,0.0002303695,0.0001164142,0.0002088753,0.0001872396,0.0001742833],"domain_scores_gemma":[0.9942359,0.003847429,0.0004074256,0.0002600674,0.0006073472,0.0006417662],"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":[0.02947336,0.0008292972,0.002370263,0.0005660719,0.0001044166,0.0008004192,0.0001281147,0.001415304,0.9543733,0.00018908,0.0003322444,0.00941809],"study_design_scores_gemma":[0.00008928852,0.001123822,0.004023651,0.00003046662,0.00005881193,0.000125165,0.00005928925,0.000841249,0.9927077,0.0000657223,0.0008490478,0.00002586626],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934881,0.002142561,0.0005509282,0.0001678734,0.0001331063,0.00004357048,0.0007779929,0.00007501994,0.002620858],"genre_scores_gemma":[0.9949318,0.0007569296,0.0008393619,0.0001326384,0.00005314982,0.00002830621,0.0006298814,0.00008259576,0.002545361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005836302,"threshold_uncertainty_score":0.01327938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111156517078915,"score_gpt":0.2118890193980573,"score_spread":0.2007774542272681,"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."}}