{"id":"W4389726142","doi":"10.12783/shm2023/37028","title":"SATELLITE MONITORING OF TRANSPORTATION INFRASTRUCTURE","year":2023,"lang":"en","type":"article","venue":"","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Infrastructure Canada; Transport Canada","keywords":"Satellite; Interferometric synthetic aperture radar; Computer science; Service (business); Remote sensing; Runway; Process (computing); Transport engineering; Engineering; Synthetic aperture radar; Geology; Geography; Business","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002545629,0.0003743862,0.0001938801,0.001896166,0.0002903283,0.0004633609,0.0002789106,0.000268519,0.001714628],"category_scores_gemma":[0.0004104471,0.00009649967,0.0001876029,0.002185785,0.0001164542,0.0004021776,0.000370479,0.0002725046,0.0007323844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004810191,"about_ca_system_score_gemma":0.0004923553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0174089,"about_ca_topic_score_gemma":0.02462658,"domain_scores_codex":[0.9996842,0.00004374074,0.00001475434,0.00007515703,0.0001410455,0.00004103172],"domain_scores_gemma":[0.9995028,0.00003030062,0.00009025939,0.00005022202,0.0002933485,0.00003305377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003079199,0.0002182702,0.2853803,0.0008794809,0.0004005391,0.0005987843,0.001183045,0.03752718,0.1250826,0.003246043,0.04169623,0.5034796],"study_design_scores_gemma":[0.00005808597,0.0005455189,0.7471138,0.0002216311,0.0002886205,0.000696421,0.001437158,0.06907465,0.03803622,0.001664026,0.1407758,0.00008825678],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7700196,0.003589741,0.05106517,0.000796888,0.0002905743,0.0004206079,0.04394614,0.002540671,0.1273306],"genre_scores_gemma":[0.9530142,0.001499337,0.01780225,0.0001611779,0.00008970677,0.00009767852,0.0186167,0.0000523528,0.008666619],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0174089,"threshold_uncertainty_score":0.03461516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622808469403458,"score_gpt":0.2798096085387127,"score_spread":0.2635815238446781,"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."}}