{"id":"W3046550518","doi":"","title":"Chemical properties of litter inputs and organic matter along the Canadian Boreal Forest Transect Case Study","year":2012,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Transect; Taiga; Environmental science; Litter; Boreal; Organic matter; Forestry; Ecology; Geography; Agroforestry; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002561637,0.0003503486,0.0002568502,0.0008425018,0.002481847,0.0006517671,0.0006697879,0.0003766666,0.0007797776],"category_scores_gemma":[0.0005072455,0.0002093199,0.0003162457,0.001501289,0.00057738,0.000305574,0.0003359477,0.0002999439,0.00008414419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008914888,"about_ca_system_score_gemma":0.007772268,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9923161,"about_ca_topic_score_gemma":0.9980146,"domain_scores_codex":[0.9997256,0.0000200433,0.00001055964,0.0000468721,0.00009788269,0.0000989892],"domain_scores_gemma":[0.9995943,0.00002482505,0.00005514348,0.00001414846,0.0002473358,0.00006419673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001937903,0.0001431945,0.9727387,0.00005723204,0.0001258775,0.001274057,0.001864352,0.00452665,0.007929534,0.0003820991,0.001545415,0.009218967],"study_design_scores_gemma":[0.000005906134,0.00002298739,0.9944301,0.0000077337,0.00003358396,0.0001763344,0.00164252,0.001613637,0.0007328873,0.00002646794,0.001292473,0.00001527258],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972436,0.00005698173,0.00007373542,0.00003456245,0.000001176241,0.00001642117,0.0007421018,0.000004378649,0.00182691],"genre_scores_gemma":[0.9980676,0.00008277702,0.0002932127,0.00001790956,8.920827e-7,0.000007738434,0.000468936,0.000002992211,0.001058045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008914888,"threshold_uncertainty_score":0.06468236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02245467692067746,"score_gpt":0.2166432315082238,"score_spread":0.1941885545875463,"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."}}