{"id":"W2063481856","doi":"10.1007/s10651-010-0137-9","title":"Modelling aboveground tree biomass while achieving the additivity property","year":2010,"lang":"en","type":"article","venue":"Environmental and Ecological Statistics","topic":"Forest ecology and management","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ministerio de Ciencia e Innovación; Interreg; Simon Fraser University; University of Oxford","keywords":"Additive function; Beech; Tree (set theory); Property (philosophy); Mathematics; Biomass (ecology); Statistics; Smoothing; Econometrics; Environmental science; Ecology; Forestry; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.004723751,0.001685279,0.001339906,0.001014848,0.0005850095,0.001813983,0.002172725,0.001108524,0.001631578],"category_scores_gemma":[0.02001988,0.001389725,0.002297101,0.001083832,0.001397387,0.00414611,0.00320284,0.002887985,0.0005116799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007563315,"about_ca_system_score_gemma":0.0009338306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00587429,"about_ca_topic_score_gemma":0.005281417,"domain_scores_codex":[0.9982179,0.0007153817,0.0001116491,0.0003354105,0.0004278062,0.0001918332],"domain_scores_gemma":[0.9895846,0.008084888,0.0006190577,0.00117948,0.000349408,0.0001824664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003774346,0.00004747722,0.00277366,0.00004923953,0.00008682573,0.0001183781,0.0000631228,0.9540346,0.002319031,0.02884007,0.0002542654,0.0113756],"study_design_scores_gemma":[0.000002741168,0.00002027466,0.0003545833,0.000003606236,0.00002318696,0.00006000171,0.000006282847,0.9849553,0.001218388,0.01306824,0.0002806074,0.000006861464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05125823,0.000127052,0.9450788,0.0002105917,0.00004086639,0.00002545401,0.0001163611,0.0003264791,0.002816115],"genre_scores_gemma":[0.8857729,0.0002917557,0.1069789,0.0002456005,0.0001753892,0.0001063201,0.0002350398,0.0003518703,0.005842166],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00587429,"threshold_uncertainty_score":0.02498192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01272920439659122,"score_gpt":0.1869536047614212,"score_spread":0.17422440036483,"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."}}