{"id":"W2903278857","doi":"10.1016/j.jcp.2019.04.065","title":"The synthesis of data from instrumented structures and physics-based models via Gaussian processes","year":2019,"lang":"en","type":"article","venue":"Journal of Computational Physics","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Innovate UK; Engineering and Physical Sciences Research Council; UK Research and Innovation; Alan Turing Institute","keywords":"Statistical physics; Gaussian process; Gaussian; Computer science; Physics; Applied mathematics; Algorithm; Mathematics; Quantum mechanics","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":[0.002112223,0.0008133042,0.0008556409,0.001002224,0.0003195391,0.001396021,0.0009840459,0.001429472,0.001530724],"category_scores_gemma":[0.01057197,0.0006884125,0.001073429,0.001035361,0.0009434804,0.002032368,0.001333068,0.001335733,0.000495634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006434065,"about_ca_system_score_gemma":0.001565365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003352838,"about_ca_topic_score_gemma":0.002601794,"domain_scores_codex":[0.999121,0.0002679185,0.00005346062,0.0001906835,0.0003011533,0.00006580951],"domain_scores_gemma":[0.9967306,0.00206759,0.0003184455,0.0005139781,0.0002972763,0.00007219454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007747303,0.0002005815,0.00520478,0.0003454356,0.000193303,0.0001908321,0.0002318159,0.8072269,0.02529957,0.04555589,0.001783608,0.1129927],"study_design_scores_gemma":[0.0000250878,0.00003421338,0.0007151093,0.000009566785,0.00001573846,0.00002354828,0.00001551081,0.9821796,0.004893298,0.01159341,0.0004764319,0.00001855275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04085561,0.000130991,0.9568136,0.0002574768,0.00006358804,0.00004455706,0.0004068004,0.0008078648,0.0006194793],"genre_scores_gemma":[0.795782,0.0004148051,0.199863,0.0001587232,0.00009393777,0.0001346599,0.001753847,0.0002960751,0.001503168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003352838,"threshold_uncertainty_score":0.01117063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03162966387907305,"score_gpt":0.2934082511981324,"score_spread":0.2617785873190593,"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."}}