{"id":"W2783575503","doi":"10.3390/f9010021","title":"Low Tree-Growth Elasticity of Forest Biomass Indicated by an Individual-Based Model","year":2018,"lang":"en","type":"article","venue":"Forests","topic":"Forest ecology and management","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service; Ministry of Forests","funders":"","keywords":"Biomass (ecology); Tsuga; Silviculture; Environmental science; Western Hemlock; Forestry; Ecology; Forest management; Competition (biology); Stand development; Biology; Geography","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":[0.0003981871,0.0004980379,0.0007149714,0.0004128715,0.0004215066,0.0009200909,0.001422555,0.00128789,0.003068958],"category_scores_gemma":[0.001216106,0.0003804186,0.0007546077,0.0004515731,0.0006353905,0.000744502,0.0005602006,0.0007485628,0.0004472843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009276037,"about_ca_system_score_gemma":0.0009583703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01869036,"about_ca_topic_score_gemma":0.01114329,"domain_scores_codex":[0.9998431,0.00004282783,0.000007157882,0.00004758341,0.00002010766,0.00003916834],"domain_scores_gemma":[0.9996075,0.0001793785,0.00007204352,0.00003231389,0.00005512422,0.00005357916],"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":[0.00002448678,0.00001948535,0.001358968,0.00001434964,0.0000185953,0.00003600821,0.00002325528,0.9943885,0.0007688065,0.002644146,0.0001450407,0.0005583],"study_design_scores_gemma":[0.00000952088,0.000007174301,0.0005895319,0.000003077541,0.000008052656,0.00001070732,0.000007181598,0.9979668,0.00005315341,0.00119522,0.0001444828,0.000004971209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8601369,0.0002580547,0.1127909,0.0007349779,0.00004946732,0.00008734286,0.001855565,0.0003438313,0.02374301],"genre_scores_gemma":[0.9893946,0.0001040325,0.00536282,0.0000721882,0.00001253411,0.0001445207,0.0002873548,0.000039672,0.004582264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01869036,"threshold_uncertainty_score":0.03716314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009404524690159764,"score_gpt":0.2236386191818562,"score_spread":0.2142340944916964,"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."}}