{"id":"W3200562876","doi":"10.3390/rs13183587","title":"Assessing the Impacts of Rising Sea Level on Coastal Morpho-Dynamics with Automated High-Frequency Shoreline Mapping Using Multi-Sensor Optical Satellites","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Coastal and Marine Dynamics","field":"Earth and Planetary Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre For Cold Ocean Resources Engineering; Memorial University of Newfoundland","funders":"U.S. Geological Survey","keywords":"Shore; Remote sensing; Sampling (signal processing); Satellite; Coastal erosion; Geology; Environmental science; Physical geography; Oceanography; Geography; Computer 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":[0.0003803957,0.000305231,0.0001513272,0.001065013,0.000155496,0.00047824,0.0001921903,0.0001616231,0.0004201783],"category_scores_gemma":[0.0006625667,0.0001417093,0.0003917946,0.0009038622,0.0001369483,0.0005359271,0.0004070532,0.0001552245,0.0001362162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000323397,"about_ca_system_score_gemma":0.0003306539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01672525,"about_ca_topic_score_gemma":0.04312572,"domain_scores_codex":[0.9997594,0.00005453447,0.00001820228,0.00005721948,0.00007450255,0.00003611618],"domain_scores_gemma":[0.9995906,0.00009786966,0.0001427638,0.00004937437,0.00008788187,0.00003154004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006805902,0.000116782,0.9223117,0.00006903006,0.0001502484,0.0001508283,0.0002204826,0.01673281,0.008468729,0.0001195976,0.0002863408,0.05130553],"study_design_scores_gemma":[0.000002933984,0.00007008513,0.9433353,0.000007535637,0.00003376253,0.00004183143,0.0003796681,0.05435651,0.001416966,0.00007288638,0.0002723299,0.00001020856],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972726,0.00002419446,0.001861317,0.0000187732,0.000002282157,0.00001044341,0.0003699161,0.00004095624,0.0003995377],"genre_scores_gemma":[0.9961632,0.00003651339,0.003137778,0.000005517515,0.000002292946,0.0000081666,0.0004962549,0.000004443967,0.0001458727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01672525,"threshold_uncertainty_score":0.03325576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04065780484685676,"score_gpt":0.2699589523704434,"score_spread":0.2293011475235867,"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."}}