{"id":"W2771496933","doi":"10.1016/j.forpol.2017.12.002","title":"Timber market actors' values on forest legislation: A case study from Colombia","year":2017,"lang":"en","type":"article","venue":"Forest Policy and Economics","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Ministry of Environment and Sustainable Development","keywords":"Legislation; Forest management; Business; Variety (cybernetics); Forest ecology; Government (linguistics); Environmental resource management; Transparency (behavior); Deforestation (computer science); Poverty; Forest product; Forestry; Geography; Economics; Ecosystem; Ecology; Political science; Economic growth","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001897568,0.0001983159,0.0001889129,0.00005822946,0.0007050626,0.0003676096,0.0003172888,0.0000763584,0.001519929],"category_scores_gemma":[0.00007150465,0.0001911345,0.00005304493,0.00003143687,0.0002589146,0.0005431185,0.0004355839,0.00009826932,0.001108864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001168524,"about_ca_system_score_gemma":0.00001368216,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05293529,"about_ca_topic_score_gemma":0.05779362,"domain_scores_codex":[0.9990271,0.00003024412,0.0002095772,0.0003582493,0.000065853,0.0003089904],"domain_scores_gemma":[0.9989053,0.00008843062,0.0001767496,0.000676433,0.00000272886,0.0001503704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006201467,0.00013405,0.9586082,0.000002752465,0.00004397854,0.00009943512,0.001193946,0.001976654,3.538264e-7,0.003340222,0.0327941,0.001744334],"study_design_scores_gemma":[0.0009987478,0.000281345,0.8853275,0.000006410296,0.00003592082,0.00003322476,0.0001218414,0.01477018,0.000001710631,0.008285289,0.08983599,0.0003018702],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8283617,0.000002850199,0.000001547497,0.000509471,0.0001485138,0.0003118037,0.0000420595,0.0000229498,0.1705991],"genre_scores_gemma":[0.9822996,0.00003096184,0.00007035751,0.00034161,0.000526875,0.00002547115,0.00001235666,0.00002191507,0.01667082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1539379,"threshold_uncertainty_score":0.9996689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02156682428687063,"score_gpt":0.2669197183203632,"score_spread":0.2453528940334925,"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."}}