{"id":"W4290994237","doi":"10.5558/tfc2022-002","title":"Enhancing forest resilience: Advances in Ontario’s wild tree seed transfer policy","year":2022,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service; Ontario Forest Research Institute; Ministry of Natural Resources and Forestry","funders":"Canadian Forest Service; Natural Resources Canada; U.S. Forest Service; Ontario Ministry of Natural Resources and Forestry; Ministry of Natural Resources","keywords":"Climate change; Environmental resource management; Procurement; Psychological resilience; Resilience (materials science); Tree (set theory); Process (computing); Productivity; Policy development; Natural resource management; Geography; Natural resource; Business; Environmental planning; Political science; Ecology; Computer science; Environmental science; Marketing; Biology; Economics; Psychology; Public administration","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.0090703,0.0003168176,0.0003002019,0.001375858,0.008400572,0.005729777,0.002719794,0.002543903,0.006430889],"category_scores_gemma":[0.01116845,0.0002807945,0.0004412605,0.001296551,0.003665019,0.002703716,0.003607073,0.002499801,0.0003541862],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09053203,"about_ca_system_score_gemma":0.2813504,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9690695,"about_ca_topic_score_gemma":0.991573,"domain_scores_codex":[0.9952056,0.0005892038,0.0001415371,0.0002744427,0.002145138,0.001644141],"domain_scores_gemma":[0.9837248,0.003324613,0.0006547087,0.0005996309,0.005348084,0.00634817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000259847,0.0004100391,0.04180297,0.001428389,0.00009227916,0.001854787,0.02159395,0.00953034,0.006231357,0.1958029,0.386301,0.3346922],"study_design_scores_gemma":[0.00004520543,0.00009263361,0.05106244,0.001082252,0.00004436606,0.0001564595,0.009717979,0.003749182,0.001264007,0.02274668,0.9098986,0.0001401625],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.1226104,0.01483377,0.009588049,0.6017412,0.001419211,0.0004721897,0.001662304,0.0005254692,0.2471474],"genre_scores_gemma":[0.8740713,0.01382639,0.02669986,0.03623802,0.0004702315,0.0002568423,0.0009094638,0.0001464997,0.04738152],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.909468,"threshold_uncertainty_score":0.6568589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004914651755092734,"score_gpt":0.2047024250432437,"score_spread":0.199787773288151,"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."}}