{"id":"W2588743658","doi":"10.1093/forestscience/56.4.356","title":"Using Linear Mixed Effects in Helicopter Logging Data","year":2010,"lang":"en","type":"article","venue":"Forest Science","topic":"Control Systems and Identification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Logging; Environmental science; Forestry; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005057977,0.00005182937,0.00006429318,0.0001170571,0.00006042679,0.00007582516,0.0004171393,0.00002491979,0.00000358258],"category_scores_gemma":[0.0001161029,0.00004875682,0.000007745014,0.0002689635,0.00006023955,0.0004903534,0.0000807988,0.00009997474,0.00003718728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002271889,"about_ca_system_score_gemma":0.00001934179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001846714,"about_ca_topic_score_gemma":0.0007630952,"domain_scores_codex":[0.999391,0.000005053835,0.0001090786,0.0001795351,0.0001344955,0.0001808073],"domain_scores_gemma":[0.9994367,0.00002294687,0.00001569375,0.0004657853,0.00001729061,0.00004157674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001082231,0.000009566673,0.01636825,0.00005330203,0.000001556055,0.000004070223,0.0001185078,0.0567967,0.9214473,0.002170591,0.0001056309,0.00292343],"study_design_scores_gemma":[0.0000961621,0.000002197255,0.04563569,0.00002701388,0.000001470375,0.00000324536,0.000004987097,0.9516534,0.001793278,0.0001491203,0.0005715537,0.00006191627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627715,0.00003636862,0.03539507,0.0000121249,0.001442937,0.0001124383,0.000002060959,0.0000534812,0.0001739646],"genre_scores_gemma":[0.997484,8.190187e-7,0.002374867,0.00000647798,0.0001094784,0.000003433103,0.00000319995,0.000006297633,0.00001147433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.919654,"threshold_uncertainty_score":0.1988245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02902284254746036,"score_gpt":0.2773849576845903,"score_spread":0.2483621151371299,"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."}}