{"id":"W3094157737","doi":"","title":"Legal, Institutional, and Economic Indicators of Forest Conservation and Sustainable Management in the United States: Analyzing Criterion 7 of the Montréal Process Criteria and Indicators Framework","year":2020,"lang":"en","type":"article","venue":"","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Process (computing); Sustainable forest management; Environmental resource management; Forest management; Business; Natural resource economics; Environmental economics; Environmental planning; Economics; Environmental science; Computer science; Agroforestry","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":[0.01405436,0.0003558948,0.00049147,0.01176634,0.003056401,0.006454668,0.001527813,0.0009636663,0.003103579],"category_scores_gemma":[0.04576249,0.0002743953,0.0006607969,0.009059822,0.00456924,0.003849936,0.002988784,0.001834288,0.0001544735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02131663,"about_ca_system_score_gemma":0.05609237,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6570505,"about_ca_topic_score_gemma":0.7655692,"domain_scores_codex":[0.9873065,0.00369822,0.0006939711,0.0004420106,0.006320405,0.001538961],"domain_scores_gemma":[0.9628479,0.01411724,0.004482422,0.0009970568,0.01579224,0.001763128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004168204,0.00008135196,0.1132693,0.00008246979,0.00006301344,0.00007312357,0.001523441,0.005953244,0.000156613,0.8391147,0.01147514,0.02816596],"study_design_scores_gemma":[0.00005049888,0.0001820297,0.6105409,0.0007849018,0.0002348811,0.0001072007,0.01195552,0.04527915,0.002532863,0.2521303,0.07602897,0.0001727067],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.456834,0.001507415,0.03512124,0.01297132,0.0001199015,0.0009173054,0.006572451,0.0001566277,0.4857996],"genre_scores_gemma":[0.9782733,0.0003637826,0.01319698,0.0003719856,0.00002675802,0.0003139392,0.001519282,0.00003107835,0.005902958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6570505,"threshold_uncertainty_score":0.6899383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008297426640122276,"score_gpt":0.2434260142680947,"score_spread":0.2351285876279724,"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."}}