{"id":"W1989101475","doi":"10.1139/x03-250","title":"Finite element modeling of guyed back spars in cable logging","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Tree Root and Stability Studies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Skyline; Structural engineering; Tension (geology); Finite element method; Stress (linguistics); Compression (physics); Transverse plane; Displacement (psychology); Point (geometry); Bending; Computer science; Engineering; Geometry; Mathematics; Materials science; Composite material","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":[0.0002778309,0.0003041272,0.0003589922,0.0003487184,0.0003313165,0.0006429471,0.0006710344,0.0008897921,0.001758627],"category_scores_gemma":[0.0006398948,0.000414552,0.0003531307,0.0002827556,0.0007254322,0.0005390271,0.0004884218,0.0004399067,0.0004265336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004004625,"about_ca_system_score_gemma":0.0006309536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006675989,"about_ca_topic_score_gemma":0.007670544,"domain_scores_codex":[0.999866,0.00003015651,0.000007664157,0.00002106613,0.00005796678,0.00001717845],"domain_scores_gemma":[0.9997968,0.0001087683,0.00002505298,0.00002226482,0.00003225092,0.00001490704],"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":[0.00001827508,0.00001560389,0.0008346348,0.00002315877,0.000005462628,0.00009148412,0.00007698198,0.9871335,0.004928092,0.001897932,0.00009261399,0.004882221],"study_design_scores_gemma":[0.000003390413,0.00001487033,0.0002675232,0.000006148232,0.000002629359,0.00003112347,0.00004391357,0.9969832,0.001327252,0.000442421,0.000872774,0.000004681282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2854816,0.0001857029,0.7017369,0.0001495929,0.00003706066,0.00008033996,0.0002477944,0.0004683984,0.01161265],"genre_scores_gemma":[0.9163643,0.0002115649,0.07367186,0.00003198283,0.000008739843,0.00007997268,0.000203968,0.00008626031,0.00934137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006675989,"threshold_uncertainty_score":0.01327425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08074138857341821,"score_gpt":0.2980383726776764,"score_spread":0.2172969841042582,"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."}}