{"id":"W4296782463","doi":"10.1146/annurev-environ-012220-010017","title":"The Role of Nature-Based Solutions in Supporting Social-Ecological Resilience for Climate Change Adaptation","year":2022,"lang":"en","type":"article","venue":"Annual Review of Environment and Resources","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":118,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais; University of British Columbia; Université du Québec à Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Natural Environment Research Council; Sight Research UK; Waterloo Foundation","keywords":"Resilience (materials science); Adaptation (eye); Psychological resilience; Environmental resource management; Climate change; Ecological systems theory; Underpinning; Ecology; Ecological resilience; Flood myth; Socio-ecological system; Environmental planning; Geography; Environmental science; Computer science; Psychology; Biology; Social psychology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001047583,0.00006465915,0.000155307,0.00001377589,0.0003936026,0.000003913838,0.000150638,0.0000306093,0.00015102],"category_scores_gemma":[0.00002215828,0.00004117953,0.00005541717,0.00007785604,0.0000612142,0.00006139709,0.0001947152,0.00007876145,0.00000162285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002789279,"about_ca_system_score_gemma":0.00000246895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005460896,"about_ca_topic_score_gemma":0.00006582827,"domain_scores_codex":[0.9990624,0.0001092663,0.0002911112,0.0001441227,0.0002062657,0.0001868007],"domain_scores_gemma":[0.9995192,0.0001361104,0.0002417647,0.00008027742,0.000002429218,0.00002025949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004600495,0.001312154,0.5846147,0.006941813,0.00005900913,0.000006573234,0.01737138,0.007104419,0.002350505,0.002239332,0.0009023259,0.3766378],"study_design_scores_gemma":[0.0006091302,0.0006792085,0.4311523,0.0005892426,0.00008400127,0.000002353749,0.01165406,0.012052,0.0002444858,0.0007714504,0.5418709,0.0002908578],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9587872,0.03847691,0.000004029384,0.001434181,0.00002249712,0.000644939,0.0001047288,0.00000446487,0.0005210426],"genre_scores_gemma":[0.9873917,0.01209526,0.00004478234,0.0002275005,0.00001394226,0.0002042497,0.00001210641,0.000003649961,0.000006825271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5409685,"threshold_uncertainty_score":0.3027312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0119154995332965,"score_gpt":0.2457681769081561,"score_spread":0.2338526773748596,"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."}}