{"id":"W4408823226","doi":"10.5194/oos2025-1270","title":"COASTS: A Digital Twin for Coastal Resilience and Blue Carbon Ecosystems","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Submarine Engineering (Canada)","funders":"","keywords":"Resilience (materials science); Ecosystem; Environmental science; Blue carbon; Oceanography; Carbon fibers; Coastal ecosystem; Psychological resilience; Environmental resource management; Fishery; Geography; Ecology; Geology; Computer science; Biology; Materials science; Psychology","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":[0.0008780056,0.0007081325,0.0003651715,0.0009737246,0.0008381387,0.004065905,0.001334602,0.00109823,0.008634633],"category_scores_gemma":[0.002670081,0.0003967081,0.0007023216,0.001346606,0.001189836,0.01045812,0.007747398,0.001792293,0.002256743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007123516,"about_ca_system_score_gemma":0.001489134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005928618,"about_ca_topic_score_gemma":0.006740021,"domain_scores_codex":[0.9996023,0.0001007604,0.00003367028,0.00007360383,0.0001419174,0.00004778934],"domain_scores_gemma":[0.9990313,0.00009334952,0.00005098397,0.0003250859,0.0001979472,0.0003013975],"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":[0.0003196226,0.0001533699,0.01291089,0.0005130925,0.0001246634,0.0009810284,0.002561607,0.04838625,0.01218825,0.3555333,0.1484246,0.4179032],"study_design_scores_gemma":[0.00004619868,0.0001359136,0.00414225,0.0003385047,0.0000975163,0.0004324786,0.001583837,0.1100219,0.004720845,0.08977339,0.7886034,0.0001037735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1096404,0.005387607,0.6319486,0.02017812,0.003196773,0.0006190843,0.007415856,0.02356029,0.1980533],"genre_scores_gemma":[0.4282857,0.007768864,0.4896394,0.001875957,0.0006344685,0.0004955317,0.009657141,0.003153322,0.05848955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008634633,"threshold_uncertainty_score":0.02888572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007247561274774801,"score_gpt":0.217393544590421,"score_spread":0.2101459833156462,"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."}}