{"id":"W4382395082","doi":"10.18280/ts.400336","title":"Advancements in Geological Disaster Monitoring and Early Warning Systems: A Deep Learning and Computer Vision Approach","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Hunan Province; Natural Science Foundation of Hainan Province; National Natural Science Foundation of China","keywords":"Deep learning; Computer science; Hyperspectral imaging; Warning system; Artificial intelligence; Data science; Remote sensing; Machine learning; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004682861,0.0004647321,0.0003323903,0.0008497018,0.0001880223,0.0008204268,0.00065495,0.0008082153,0.000896856],"category_scores_gemma":[0.0008226505,0.0002184677,0.0003203199,0.0009447595,0.0004902876,0.001405066,0.0009495735,0.001451442,0.0002861283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005760185,"about_ca_system_score_gemma":0.000709136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002467031,"about_ca_topic_score_gemma":0.002528073,"domain_scores_codex":[0.9998034,0.00004242915,0.00001348894,0.00004104412,0.00007127093,0.00002847027],"domain_scores_gemma":[0.999764,0.00007572971,0.00003586215,0.00002842083,0.00007251267,0.00002347944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000783248,0.0001430172,0.002610382,0.0003545466,0.00007742344,0.0001139643,0.000128751,0.2143985,0.0140571,0.09127263,0.006525692,0.6702397],"study_design_scores_gemma":[0.000005813911,0.00004599334,0.0009110277,0.0000516938,0.00002007936,0.00006393994,0.00003877332,0.9465849,0.005330291,0.03403134,0.01290108,0.00001514545],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.015839,0.007791603,0.9666044,0.003298478,0.0001578173,0.00002973246,0.00008318808,0.0003354191,0.00586049],"genre_scores_gemma":[0.5806224,0.01589439,0.3933468,0.000798877,0.0004905876,0.000065131,0.0003325713,0.00005848559,0.008390755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002467031,"threshold_uncertainty_score":0.004905343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0178093847987782,"score_gpt":0.2406793921499505,"score_spread":0.2228700073511724,"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."}}