{"id":"W6959926767","doi":"10.13140/rg.2.1.1646.4808","title":"Climate Change and Forest Management in Canada: Impacts, Adaptive Capacity and Adaptation options","year":2010,"lang":"en","type":"other","venue":"","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climate change; Adaptation (eye); Forest management; Climate change adaptation; Adaptive capacity; Adaptive management","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":[0.0003490537,0.0002857241,0.0002468539,0.0009659942,0.002591931,0.001938031,0.0006764472,0.0005838528,0.008686072],"category_scores_gemma":[0.001092358,0.0001318057,0.0003364519,0.003260372,0.0008106109,0.0004797333,0.0008555517,0.000614462,0.0003703433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04172362,"about_ca_system_score_gemma":0.07193055,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9982051,"about_ca_topic_score_gemma":0.9995034,"domain_scores_codex":[0.9996148,0.00003378949,0.00001120715,0.00003710105,0.0001100465,0.0001930665],"domain_scores_gemma":[0.9993368,0.00005291976,0.00004767311,0.00001379788,0.0003118458,0.000236973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008002312,0.0002015202,0.5801578,0.0004538091,0.0002392091,0.0009000911,0.002727444,0.009060335,0.002266416,0.01411384,0.07222658,0.3168527],"study_design_scores_gemma":[0.00004746776,0.00003908958,0.9135405,0.0002376337,0.000108254,0.0001844876,0.007595421,0.003978045,0.0005103538,0.003333617,0.07034558,0.00007958927],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.8236942,0.0255431,0.0008140962,0.02102318,0.0002125552,0.0001009217,0.01863293,0.0001675043,0.1098114],"genre_scores_gemma":[0.9330279,0.01373174,0.001082942,0.001140713,0.00003921783,0.00002356639,0.002750077,0.00004530194,0.04815862],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04172362,"threshold_uncertainty_score":0.3027275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05046192443430707,"score_gpt":0.2097235028461853,"score_spread":0.1592615784118782,"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."}}