{"id":"W4403340205","doi":"10.1016/j.forpol.2024.103341","title":"Forest sector models for tropical countries - A case study of Colombia","year":2024,"lang":"en","type":"article","venue":"Forest Policy and Economics","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Amorfix (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tropical forest; Tropics; Developing country; Geography; Natural resource economics; Regional science; Agroforestry; Economics; Economic growth; Environmental science; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004792136,0.0005299879,0.0004276176,0.0006990633,0.0006030742,0.001317408,0.0007092786,0.0006882446,0.004176176],"category_scores_gemma":[0.001812755,0.000195276,0.0006079247,0.00105873,0.0004177594,0.0006837014,0.0006078586,0.0006235844,0.0002344199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003542192,"about_ca_system_score_gemma":0.001224222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.212494,"about_ca_topic_score_gemma":0.1885504,"domain_scores_codex":[0.9997732,0.0001102053,0.00001391885,0.00003639588,0.00001878536,0.00004738961],"domain_scores_gemma":[0.9990522,0.0005908683,0.0001440834,0.00004401914,0.00009722508,0.00007163098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002392766,0.000241254,0.06267473,0.0004531938,0.0001104187,0.001100892,0.0008927819,0.8503625,0.0005951147,0.05582238,0.005413894,0.02209368],"study_design_scores_gemma":[0.00008419126,0.00008797373,0.02897465,0.0001016758,0.0000771573,0.0001866146,0.001607527,0.9416233,0.0002536183,0.01144521,0.01549675,0.00006119609],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.932313,0.003901055,0.01863619,0.001562318,0.00004182288,0.0001899909,0.005589386,0.0002660031,0.03750033],"genre_scores_gemma":[0.9915282,0.0007489398,0.004079395,0.00003128783,0.00001255776,0.00006050105,0.001086739,0.00002066879,0.002431773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.212494,"threshold_uncertainty_score":0.4225143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259291047067243,"score_gpt":0.2554807435377831,"score_spread":0.2328878330671106,"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."}}