{"id":"W2029717096","doi":"10.1080/10824000209480577","title":"An Integrated Approach for Evaluating Adaptation Options to Reduce Climate Change Vulnerability in Coastal Region of the Georgia Basin","year":2002,"lang":"en","type":"article","venue":"Annals of GIS","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; University of British Columbia","funders":"","keywords":"Adaptation (eye); Multiple-criteria decision analysis; Vulnerability (computing); Analytic hierarchy process; Stakeholder; Environmental resource management; Climate change; Identification (biology); Computer science; Vulnerability assessment; Process (computing); Stakeholder engagement; Environmental planning; Environmental science; Operations research; Engineering; Psychological resilience; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.004445857,0.001241634,0.0008527848,0.009244295,0.001232505,0.003705969,0.001217068,0.001170357,0.003444295],"category_scores_gemma":[0.00442039,0.0004973063,0.001405526,0.003745002,0.0008659541,0.00113039,0.002962791,0.0008021222,0.0001538187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006645276,"about_ca_system_score_gemma":0.007930697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03334331,"about_ca_topic_score_gemma":0.0734978,"domain_scores_codex":[0.9958282,0.002383548,0.0001512537,0.0002350903,0.001078973,0.0003228748],"domain_scores_gemma":[0.9980574,0.0007036609,0.0001774019,0.00007968141,0.0008136398,0.0001681154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003621565,0.0007680106,0.03642069,0.001198985,0.001032306,0.001658333,0.003572104,0.5773208,0.01355495,0.05117569,0.004722209,0.3082137],"study_design_scores_gemma":[0.0001011877,0.0007515909,0.02782677,0.0007853233,0.0007601713,0.0002925106,0.01180451,0.8994883,0.004482986,0.03537545,0.01817087,0.0001602639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4615666,0.001410846,0.4512148,0.002132184,0.000117084,0.002699768,0.001074249,0.0007654167,0.07901905],"genre_scores_gemma":[0.7151171,0.0004863096,0.2804799,0.0001231577,0.00001381478,0.0006480697,0.0003009868,0.0000326207,0.00279802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03334331,"threshold_uncertainty_score":0.06629848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1954873204298355,"score_gpt":0.3453626609146572,"score_spread":0.1498753404848218,"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."}}