{"id":"W4389561507","doi":"10.7185/gold2023.18765","title":"Quantifying the role of biogeochemical interaction between macro- and micronutrients on carbon cycling in mangroves soil","year":2023,"lang":"en","type":"article","venue":"","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biogeochemical cycle; Mangrove; Carbon cycle; Cycling; Environmental science; Macro; Soil carbon; Carbon fibers; Nutrient cycle; Ecology; Environmental chemistry; Earth science; Soil science; Ecosystem; Chemistry; Soil water; Computer science; Geology; Forestry; Geography; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.000274935,0.0002136307,0.0001790032,0.0002741273,0.0002631741,0.0005567157,0.0002329439,0.0002838964,0.0004060515],"category_scores_gemma":[0.0004163105,0.0001405908,0.0001948115,0.0002334671,0.0001952053,0.000530345,0.0002238539,0.0001335389,0.00006876962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006127385,"about_ca_system_score_gemma":0.0004547308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03356799,"about_ca_topic_score_gemma":0.06721948,"domain_scores_codex":[0.9999152,0.0000134691,0.000005495344,0.00003751975,0.00001164314,0.00001662847],"domain_scores_gemma":[0.9998223,0.00007803594,0.00003364539,0.00001387236,0.00002322164,0.00002896254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002712432,0.0001091272,0.8426028,0.00009252661,0.0002253423,0.00008787714,0.0001281207,0.01186515,0.1331635,0.0003070196,0.00008710211,0.01106013],"study_design_scores_gemma":[0.000005464896,0.00003897676,0.9560806,0.000005636392,0.00003983925,0.00002727039,0.0001194327,0.036956,0.006342893,0.0001533389,0.0002214498,0.000009026069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994961,0.00003963704,0.0001989613,0.000008374192,7.428118e-7,0.000001944763,0.00008907708,0.000003970584,0.0001612346],"genre_scores_gemma":[0.9994592,0.00002763649,0.0003420695,0.000004655544,8.860975e-7,0.000002350014,0.00007208018,0.00000212654,0.00008905443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03356799,"threshold_uncertainty_score":0.06674522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01503150872661918,"score_gpt":0.247562038330342,"score_spread":0.2325305296037228,"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."}}