{"id":"W2170775372","doi":"10.1139/x02-122","title":"Predicting basal area increment in a spatially explicit, individual tree model: a test of competition measures with black spruce","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Basal area; Black spruce; Competition (biology); Range (aeronautics); Mathematics; Tree (set theory); Statistics; Predictability; Cunninghamia; Forestry; Ecology; Geography; Biology; Taiga; Botany","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001017673,0.0004849864,0.0003715428,0.00029473,0.0003198119,0.0004682692,0.0007208799,0.0003778642,0.0003217603],"category_scores_gemma":[0.001206919,0.0001950881,0.0003561771,0.000271559,0.0003171684,0.0003498865,0.0002788621,0.0003056058,0.00005964075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001373863,"about_ca_system_score_gemma":0.001722736,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.378176,"about_ca_topic_score_gemma":0.3594251,"domain_scores_codex":[0.9998478,0.00004852324,0.000007555675,0.00004638703,0.00001990087,0.00002988022],"domain_scores_gemma":[0.9992259,0.0004660985,0.000081701,0.00005038279,0.00009658742,0.00007932739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003355798,0.0001556024,0.1085163,0.00001851143,0.0001012822,0.00005019968,0.00006822652,0.8806936,0.002456192,0.0002068494,0.00007871217,0.007318894],"study_design_scores_gemma":[0.000009480562,0.00007436771,0.01455495,0.000001511472,0.00001032356,0.000009085296,0.00002290212,0.9848713,0.0003695356,0.0000416184,0.00002866445,0.000006219278],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986026,0.00001888648,0.001215108,0.00001012445,8.93999e-7,0.000003104045,0.00003064859,0.00001444153,0.0001041561],"genre_scores_gemma":[0.9983272,0.00001197236,0.001439556,0.000004756056,0.000001204407,0.000004035327,0.00006614964,0.000003051113,0.0001420852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.621824,"threshold_uncertainty_score":0.7519495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0449669392887848,"score_gpt":0.2602549719486108,"score_spread":0.215288032659826,"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."}}