{"id":"W2161860530","doi":"10.1007/s00226-004-0269-x","title":"Models for predicting lumber bending MOR and MOE based on tree and stand characteristics in black spruce","year":2005,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Forest ecology and management","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"Intertek (Canada)","funders":"","keywords":"Seemingly unrelated regressions; Mathematics; Ordinary least squares; Least-squares function approximation; Regression; Statistics; Applied mathematics; Simultaneous equations; Regression analysis; Mathematical analysis; Differential equation","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":[0.00130847,0.0007563907,0.0005049846,0.0005219523,0.000464431,0.0006579407,0.0007592157,0.0006777766,0.0009784162],"category_scores_gemma":[0.001527374,0.0005586183,0.000613943,0.0002814528,0.0002815231,0.0005053108,0.0003216134,0.000572941,0.0003080901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008940903,"about_ca_system_score_gemma":0.0005810288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03848378,"about_ca_topic_score_gemma":0.05237411,"domain_scores_codex":[0.9998748,0.00003600726,0.000007507689,0.00003398017,0.0000147236,0.00003283232],"domain_scores_gemma":[0.9985486,0.001083773,0.00009495749,0.00003094745,0.0001279638,0.0001136986],"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":[0.0004455473,0.0002327839,0.1004374,0.00002490313,0.0001660514,0.00007649045,0.00007694333,0.8789184,0.004115986,0.0002185929,0.0006044255,0.01468245],"study_design_scores_gemma":[0.00000536045,0.0000266956,0.01082901,0.00000204017,0.00001639442,0.00000926489,0.00002017884,0.9885407,0.0003600747,0.0001563992,0.0000282748,0.00000567621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887614,0.0001035767,0.01041034,0.00006615641,0.00001119193,0.000007972618,0.0002196648,0.0001468999,0.0002728881],"genre_scores_gemma":[0.9955127,0.00005705418,0.00300487,0.00001791728,0.000008936178,0.00001546789,0.0003969339,0.00002084941,0.0009653122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03848378,"threshold_uncertainty_score":0.07651955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008486217752228162,"score_gpt":0.2196037443771012,"score_spread":0.211117526624873,"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."}}