{"id":"W2044166085","doi":"10.1016/j.forpol.2005.01.005","title":"Inter-regional comparisons of production technology in Canada's timber harvesting industries","year":2005,"lang":"en","type":"article","venue":"Forest Policy and Economics","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Production (economics); Productivity; Economics; Capital (architecture); Agricultural economics; Logging; Technical change; Total factor productivity; Technological change; Production function; Microeconomics; Forestry; Geography; Economic growth; Macroeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006474264,0.00007358337,0.0001074988,0.0001113828,0.00003902721,0.000008670548,0.0001004587,0.00004225467,0.0001078676],"category_scores_gemma":[0.00004013669,0.00007765384,0.00000920107,0.0001618862,0.0001785188,0.0001619117,0.0001251066,0.0000859431,0.00003664369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003274044,"about_ca_system_score_gemma":0.00009272749,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7809128,"about_ca_topic_score_gemma":0.9717506,"domain_scores_codex":[0.9994664,0.000006274492,0.0001865961,0.0001347682,0.00002583588,0.000180193],"domain_scores_gemma":[0.9997622,0.00001486759,0.00007848768,0.0001062689,0.000002059373,0.00003610623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008056528,0.00001807964,0.9163406,0.00000552864,0.000005442309,3.827427e-7,0.0001004853,0.04396572,0.000006088096,0.01218123,0.01838895,0.008979468],"study_design_scores_gemma":[0.0003355334,0.00003804007,0.4009866,0.0000234622,0.000006765499,0.00001831972,0.0001276359,0.02000203,0.0002410817,0.002504463,0.5754939,0.000222095],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818956,0.000009020844,0.000003476629,0.009943132,0.00003267342,0.00007685319,0.000004773456,0.000007377176,0.008027133],"genre_scores_gemma":[0.9972461,0.00002389197,0.000273246,0.000215491,0.0001038379,0.000006136171,0.00000504726,0.000005365664,0.002120859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.557105,"threshold_uncertainty_score":0.3166631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01748156830963444,"score_gpt":0.2190567064249633,"score_spread":0.2015751381153288,"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."}}