{"id":"W4320735651","doi":"10.2139/ssrn.4357883","title":"Determining Synergies and Trade-Offs between Adaptation, Mitigation and Development in Coastal Socioecological Systems in Bangladesh","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Adaptation (eye); Climate change adaptation; Business; Environmental resource management; Geography; Environmental science; Ecology; Climate change","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001759739,0.0003562538,0.0004449477,0.002015411,0.00117275,0.002291347,0.0006206426,0.0005997061,0.002967461],"category_scores_gemma":[0.004359047,0.0003352354,0.0003832052,0.002463233,0.00173299,0.001295935,0.003022512,0.000485249,0.0002333852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007047636,"about_ca_system_score_gemma":0.003366742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06215547,"about_ca_topic_score_gemma":0.1479765,"domain_scores_codex":[0.9982011,0.0008275902,0.0001396798,0.0001923376,0.0001480569,0.0004912197],"domain_scores_gemma":[0.9971283,0.001216695,0.0005970444,0.0001022035,0.0003408911,0.0006148001],"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":[0.000370735,0.000120115,0.973727,0.0001113417,0.0002430456,0.0004768935,0.003477219,0.003760026,0.001956676,0.003021312,0.0001767715,0.01255878],"study_design_scores_gemma":[0.0000126859,0.0002059588,0.9752775,0.00003410888,0.00007750358,0.00009508824,0.01909581,0.003135459,0.0002089331,0.001212331,0.0006219276,0.00002267223],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977145,0.00008014085,0.00008730107,0.0001166393,0.000001013875,0.00001953584,0.00008233981,0.00000139204,0.001897113],"genre_scores_gemma":[0.9998024,0.00002783365,0.00005214342,0.000004345126,3.738187e-7,0.000007835695,0.00001917613,3.186974e-7,0.00008567859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06215547,"threshold_uncertainty_score":0.1235874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01358889912215357,"score_gpt":0.2207747830873148,"score_spread":0.2071858839651612,"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."}}