{"id":"W2290961178","doi":"","title":"Business environment description for softwood lumbers production in Brazil and Canada.","year":2011,"lang":"en","type":"article","venue":"FLORESTA","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Production (economics); Softwood; Business; Forensic engineering; Pulp and paper industry; Waste management; Engineering; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002642429,0.0003035676,0.0001216406,0.002013772,0.001078228,0.001181357,0.0005354155,0.0001786147,0.02106552],"category_scores_gemma":[0.0006971539,0.0001133731,0.0002911224,0.003384232,0.0001853438,0.0004997989,0.0003979275,0.0003202693,0.00309148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007311795,"about_ca_system_score_gemma":0.01196616,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.846115,"about_ca_topic_score_gemma":0.9200673,"domain_scores_codex":[0.9995964,0.00002254562,0.00001302061,0.000030181,0.0001937729,0.0001441347],"domain_scores_gemma":[0.9992517,0.00007471233,0.00005287051,0.00002633675,0.0004562652,0.0001381434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006671505,0.0004848017,0.147121,0.001372632,0.00005452261,0.002809655,0.002725672,0.01910172,0.01546842,0.02444385,0.2767091,0.5090415],"study_design_scores_gemma":[0.00001820104,0.00005817329,0.278959,0.0001828219,0.00001729343,0.0003029265,0.004350654,0.003239965,0.002551596,0.0006481664,0.7096207,0.00005055672],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2423401,0.002092994,0.008785179,0.001525026,0.0001640293,0.001222467,0.1995135,0.001564524,0.5427923],"genre_scores_gemma":[0.5809605,0.002979598,0.01542696,0.0003933646,0.0000290745,0.0005841534,0.08028992,0.0004870258,0.3188494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.153885,"threshold_uncertainty_score":0.3095825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01425389124976913,"score_gpt":0.1658338319681487,"score_spread":0.1515799407183796,"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."}}