{"id":"W4402995291","doi":"10.3390/f15101722","title":"Assessing Vulnerability to Cyclone Hazards in the World’s Largest Mangrove Forest, The Sundarbans: A Geospatial Analysis","year":2024,"lang":"en","type":"article","venue":"Forests","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Shahjalal University of Science and Technology; National Geographic Society; Asia-Pacific Network for Global Change Research","keywords":"Mangrove; Geospatial analysis; Vulnerability (computing); Geography; Environmental science; Forestry; Environmental resource management; Agroforestry; Ecology; Remote sensing","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":[0.0002657543,0.000316398,0.0001934521,0.004589577,0.0004694327,0.0008542613,0.0001991452,0.0001993344,0.0007949437],"category_scores_gemma":[0.0008546904,0.0001181089,0.0004665664,0.004334293,0.0002980476,0.0004217385,0.0007046423,0.0001813022,0.0001216921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006257216,"about_ca_system_score_gemma":0.0005057505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08225967,"about_ca_topic_score_gemma":0.116466,"domain_scores_codex":[0.9998004,0.00004498526,0.00002092564,0.00002961758,0.00005809823,0.00004603234],"domain_scores_gemma":[0.9994253,0.0001550552,0.0001856055,0.00004299466,0.0001097956,0.00008119567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004160714,0.00005495265,0.9867162,0.00002490259,0.00009717231,0.000367226,0.0005566997,0.003760986,0.0008572745,0.0002330147,0.0003374351,0.006952552],"study_design_scores_gemma":[0.000001591937,0.00002058482,0.9883969,0.00001027722,0.00003144363,0.0001162938,0.002064091,0.008687148,0.0001188703,0.00007336117,0.0004718209,0.000007612544],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985949,0.00004731806,0.0002105367,0.00002294813,0.000001286146,0.00001087864,0.0006493012,0.00001037142,0.0004523275],"genre_scores_gemma":[0.99845,0.0000708013,0.0004942485,0.000003194348,0.000002126008,0.000009996097,0.0008406632,0.000002050705,0.0001269106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08225967,"threshold_uncertainty_score":0.1635617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01005445695474061,"score_gpt":0.2883367174664159,"score_spread":0.2782822605116753,"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."}}