{"id":"W2914315871","doi":"10.1139/er-2018-0102","title":"How do community-level climate change vulnerability assessments treat future vulnerability and integrate diverse datasets? A review of the literature","year":2019,"lang":"en","type":"review","venue":"Environmental Reviews","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McGill University","funders":"United States Agency for International Development","keywords":"Vulnerability (computing); Climate change; Vulnerability assessment; Temporal scales; Environmental resource management; Judgement; Geography; Computer science; Environmental science; Psychological resilience; Ecology; Psychology; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.006229468,0.0007698153,0.002571851,0.00008645276,0.0009888811,0.0002318502,0.001079632,0.0004542692,0.0002126284],"category_scores_gemma":[0.0005654406,0.0004751424,0.000852585,0.0006066328,0.0006683561,0.0008565965,0.0006570073,0.001484392,0.00006563774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009103916,"about_ca_system_score_gemma":0.00008976223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002282597,"about_ca_topic_score_gemma":0.0009064508,"domain_scores_codex":[0.9861092,0.01080192,0.001145856,0.0007368654,0.0007412069,0.0004649268],"domain_scores_gemma":[0.9955577,0.0004741079,0.001781319,0.001994556,0.00001629891,0.0001759753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003475344,0.0001709854,0.0002724775,0.07649398,0.00003002008,7.863484e-7,0.003170516,2.597899e-9,6.513145e-7,0.00003440542,0.001894775,0.9179279],"study_design_scores_gemma":[0.0001298291,0.00004514448,0.00042865,0.07823987,0.0009395096,0.00000526069,0.002046244,3.92581e-7,2.951077e-7,0.00002064737,0.9177688,0.0003753157],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000106893,0.9796847,0.000001568052,0.0004740441,0.0005114442,0.007277353,0.01163474,0.00001944997,0.0002897822],"genre_scores_gemma":[0.00003403279,0.991416,0.0001287151,0.0003940891,0.000309377,0.0006766198,0.006739376,0.00003784459,0.0002639861],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9175526,"threshold_uncertainty_score":0.99977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3102255815818226,"score_gpt":0.4197292088504104,"score_spread":0.1095036272685879,"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."}}