{"id":"W1561322135","doi":"10.22230/jem.2011v12n1a89","title":"A Vulnerability-Based Strategy for Incorporating the Climate Threat in Conservation Planning: A Case Study from the British Columbia Central Interior","year":2011,"lang":"en","type":"article","venue":"Journal of Ecosystems and Management","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nature Conservancy of Canada","funders":"Ministry of Environment; Ministry of Forests, Lands and Natural Resource Operations","keywords":"Vulnerability (computing); Climate change; Environmental resource management; Context (archaeology); Vulnerability assessment; Geography; Adaptive capacity; Environmental planning; Environmental science; Ecology; Computer science; Psychological resilience","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008709929,0.00006219312,0.0001331841,0.000008137024,0.0003100472,0.0003794736,0.0001225655,0.000019108,0.0006447198],"category_scores_gemma":[0.00001350563,0.00004869624,0.0000420125,0.00007566653,0.00004306603,0.0001132852,0.00005861214,0.00007560211,0.000001171816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303817,"about_ca_system_score_gemma":0.000005283137,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08099005,"about_ca_topic_score_gemma":0.5711648,"domain_scores_codex":[0.9991185,0.0001025472,0.0003873053,0.0001176752,0.0001259667,0.000148006],"domain_scores_gemma":[0.9994855,0.00006602511,0.0002876166,0.0001047233,0.00001600259,0.00004012986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004569966,0.0001356688,0.9947107,0.00002940572,0.00002888649,0.000462651,0.0008510489,0.0000556424,0.000007716078,0.00002367942,0.002076294,0.001572602],"study_design_scores_gemma":[0.001240963,0.000304574,0.9391528,0.00009760654,0.00004672696,0.0001502934,0.05610279,0.001711908,0.000002140536,0.0001273765,0.0009911727,0.00007160157],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981182,0.00005695542,0.0001765251,0.0001219824,0.0001393788,0.0007982091,0.00004106253,0.000004021793,0.000543648],"genre_scores_gemma":[0.9996812,0.00001660705,0.00006216243,0.0001570272,0.00002469537,0.00003626974,0.000004565642,0.000004030373,0.00001348576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4901748,"threshold_uncertainty_score":0.9251297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07338746100697163,"score_gpt":0.2722202877234321,"score_spread":0.1988328267164605,"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."}}