{"id":"W4390661331","doi":"10.1016/j.ijdrr.2024.104256","title":"Evaluating resilience of coastal communities upon integrating PRISMA protocol, composite resilience index and analytical hierarchy process","year":2024,"lang":"en","type":"article","venue":"International Journal of Disaster Risk Reduction","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University; St. Mary's University","funders":"University Grants Commission of Bangladesh","keywords":"Resilience (materials science); Index (typography); Process (computing); Hierarchy; Analytic hierarchy process; Protocol (science); Composite index; Environmental resource management; Environmental science; Computer science; Engineering; Risk analysis (engineering); Business; Composite indicator; Operations research; Political science; Medicine; Materials science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009085932,0.0001301922,0.000160149,0.0001976218,0.0000942729,0.0001736656,0.0003766712,0.00003777148,0.000117928],"category_scores_gemma":[0.00006376001,0.0001015319,0.00006933216,0.0002044564,0.0002926313,0.0009888643,0.0002367269,0.0003704345,0.000004216059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001207985,"about_ca_system_score_gemma":0.00004147213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003145075,"about_ca_topic_score_gemma":0.00008199619,"domain_scores_codex":[0.9979654,0.0001751719,0.0006017723,0.0001671919,0.0009560597,0.0001344129],"domain_scores_gemma":[0.999202,0.00008592461,0.00042249,0.0001076648,0.0001205082,0.00006141907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001525829,0.0006175335,0.2454684,0.000222018,0.0004141037,0.00004977261,0.0259968,0.1001997,0.0188777,0.001076346,0.0007340419,0.6048177],"study_design_scores_gemma":[0.002213414,0.001921335,0.09259894,0.002382266,0.000223563,0.0006601874,0.03919145,0.843496,0.007166884,0.007538765,0.002086136,0.0005211282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986183,0.00003019269,0.01032925,0.0003396136,0.000374495,0.001746632,0.000006380685,0.00001406069,0.000976313],"genre_scores_gemma":[0.9963681,0.00004085497,0.003120822,0.00001056943,0.0001158992,0.0002125148,0.000003068541,0.00001005099,0.0001181155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7432962,"threshold_uncertainty_score":0.414035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02038098108693455,"score_gpt":0.3675430392065342,"score_spread":0.3471620581195997,"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."}}