{"id":"W2998617041","doi":"","title":"Climate Change – Impact on the Sundarbans, a Case Study","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Water-Energy-Food Nexus Studies","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mangrove; Climate change; Geography; Environmental protection; Threatened species; Monsoon; Global warming; Agroforestry; Natural resource economics; Habitat; Ecology; Environmental 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002463876,0.0002906986,0.0001961114,0.0008056812,0.003630532,0.001533732,0.0005774109,0.001058416,0.003599845],"category_scores_gemma":[0.0004800729,0.0001421274,0.000345925,0.001656218,0.001089016,0.0006986251,0.001593536,0.001284466,0.0002838899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00212446,"about_ca_system_score_gemma":0.001625899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08723436,"about_ca_topic_score_gemma":0.1796406,"domain_scores_codex":[0.9997638,0.00008236593,0.00001167415,0.00001827684,0.00003217609,0.00009172299],"domain_scores_gemma":[0.9996934,0.0000690088,0.00005850041,0.00001244752,0.00004582284,0.0001208192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003507041,0.001920002,0.3749979,0.001352486,0.00018984,0.3288911,0.1528858,0.006379738,0.003891567,0.02391426,0.03864735,0.0665792],"study_design_scores_gemma":[0.00003503379,0.0003769574,0.3093948,0.0006301823,0.00009742687,0.03097925,0.5187926,0.002876277,0.0009201071,0.003209276,0.1326151,0.00007289667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744172,0.001812935,0.0001867598,0.003476326,0.00007146154,0.00004469198,0.0003199988,0.00001109925,0.0196595],"genre_scores_gemma":[0.9895542,0.003491849,0.0002986431,0.0004803269,0.00005320992,0.00001979472,0.000175384,0.000008672326,0.005918061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08723436,"threshold_uncertainty_score":0.1734532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02809758377163705,"score_gpt":0.2752666234387453,"score_spread":0.2471690396671082,"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."}}