{"id":"W2051179653","doi":"10.4067/s0718-221x2007000100004","title":"Exportación de madera aserrada de conífera chilena. Un análisis de su competitividad","year":2009,"lang":"es","type":"article","venue":"Maderas Ciencia y tecnología","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Latin Americans; Geography; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008213182,0.000863504,0.0008377202,0.000549301,0.0009464862,0.001782223,0.001356254,0.0005954679,0.001786987],"category_scores_gemma":[0.000297747,0.0009160158,0.0003893166,0.001422833,0.0003753502,0.001227739,0.0002853267,0.0008783902,0.0004907606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004167414,"about_ca_system_score_gemma":0.0003645545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005947562,"about_ca_topic_score_gemma":0.00004893537,"domain_scores_codex":[0.9950104,0.0001606978,0.0007680786,0.001111025,0.000661715,0.00228807],"domain_scores_gemma":[0.9981716,0.0001408361,0.0004765288,0.0007648024,0.0002651401,0.0001810983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001798009,0.001669883,0.6518863,0.0004575906,0.0002517729,0.001216356,0.0005221953,0.0003073,0.01336611,0.297509,0.00452865,0.02810501],"study_design_scores_gemma":[0.001442491,0.0001443988,0.8865166,0.0005344677,0.0002514354,0.0001562506,0.00125992,0.0008592476,0.004299101,0.008098692,0.09527991,0.001157452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418145,0.003152288,0.001205365,0.01526194,0.0004258348,0.0005686189,0.0000584855,0.0006501784,0.03686281],"genre_scores_gemma":[0.9768143,0.0005191008,0.0007947271,0.01996932,0.001337329,0.00004284989,0.00007776247,0.00007030099,0.0003742907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2894104,"threshold_uncertainty_score":0.999329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01154499991731916,"score_gpt":0.2248965307300203,"score_spread":0.2133515308127011,"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."}}