{"id":"W3096490894","doi":"","title":"Response and development: Canada's forestry under global climate change.","year":2017,"lang":"en","type":"article","venue":"Shijie linye yanjiu","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climate change; Forestry; Agroforestry; Geography; Environmental resource management; Environmental protection; Environmental science; Ecology; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002698503,0.0001534269,0.0001115078,0.00001431607,0.0006411121,0.0001282118,0.0003998341,0.00006071421,0.0006098791],"category_scores_gemma":[0.00004643833,0.0001427194,0.00001774304,0.00004644904,0.0001908181,0.0002593293,0.0006907119,0.00007295253,0.0004678439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002219501,"about_ca_system_score_gemma":0.00006480148,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2291336,"about_ca_topic_score_gemma":0.6059447,"domain_scores_codex":[0.9988608,0.0000324917,0.0001391931,0.0002725313,0.0002545681,0.0004404643],"domain_scores_gemma":[0.9992927,0.00002365634,0.00009607264,0.0004180102,0.000003543032,0.0001660049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002148822,0.00002963065,0.9509937,0.00002101647,0.00001960618,0.00005997894,0.000297287,0.00002914531,0.00001779939,0.003960171,0.02370184,0.02065491],"study_design_scores_gemma":[0.000253108,0.00001779477,0.8106178,0.00001233278,0.000005593717,0.000003243075,0.00002129285,0.00008987241,0.00002350464,0.0004184995,0.1883723,0.0001646211],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9440697,0.0000433328,0.000005262868,0.00337236,0.0002270919,0.0001754508,0.00002222564,0.000031916,0.05205267],"genre_scores_gemma":[0.9953002,0.00002308394,0.0004127775,0.001739678,0.00009174689,0.0000165702,0.000007012071,0.00001188307,0.002397099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3768111,"threshold_uncertainty_score":0.7759997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02613773301458203,"score_gpt":0.2631267949116248,"score_spread":0.2369890618970427,"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."}}