{"id":"W1990392209","doi":"10.1139/x05-019","title":"Plot size related measurement error bias in tree growth models","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Plot (graphics); Statistics; Mathematics; Tree (set theory); Sample size determination; Combinatorics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.08722643,0.001182639,0.00233712,0.001461685,0.001030422,0.00227401,0.003477001,0.002961712,0.001979115],"category_scores_gemma":[0.2846509,0.00129231,0.001955514,0.003605028,0.002794953,0.003422146,0.002241087,0.00275042,0.0007278423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002169494,"about_ca_system_score_gemma":0.001334179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01019778,"about_ca_topic_score_gemma":0.008813838,"domain_scores_codex":[0.9465826,0.03902979,0.002699528,0.00638761,0.004279846,0.001020666],"domain_scores_gemma":[0.7189154,0.2406231,0.01352444,0.01936085,0.007156261,0.0004200254],"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":[0.001304306,0.0004074035,0.3117583,0.0009185061,0.003384353,0.001180392,0.002010979,0.3845919,0.002587781,0.1109781,0.0101588,0.1707191],"study_design_scores_gemma":[0.0002530122,0.0003742274,0.06194171,0.0003561516,0.0008073929,0.000814689,0.000325078,0.7615781,0.004316257,0.1582137,0.01083632,0.000183176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06151897,0.002295892,0.9308918,0.001335309,0.000347015,0.0003047189,0.0007537472,0.000995851,0.001556811],"genre_scores_gemma":[0.7742323,0.001037607,0.215843,0.0007987705,0.000233776,0.0007695823,0.001352403,0.0005076303,0.005224877],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08722643,"threshold_uncertainty_score":0.4613029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161552179940474,"score_gpt":0.2948677741699055,"score_spread":0.1787125561758581,"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."}}