{"id":"W3090166568","doi":"10.1016/j.heliyon.2020.e05147","title":"Sequential estimation of the generated curing heat of composite materials by data assimilation: A numerical study","year":2020,"lang":"en","type":"article","venue":"Heliyon","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Science and Technology Agency; Swine Innovation Porc","keywords":"Curing (chemistry); Materials science; Composite number; Data assimilation; Composite material; Kalman filter; Assimilation (phonology); Mathematics; Statistics; Meteorology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008015645,0.00006153488,0.0001254196,0.0000039781,0.00005930383,0.000009973265,0.0002071006,0.00001571725,0.0002616761],"category_scores_gemma":[0.00001824799,0.00004272315,0.00001386373,0.0001294389,0.00005086795,0.0001046099,0.0004152556,0.00003053433,0.00001642536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001312182,"about_ca_system_score_gemma":0.000003498692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006545294,"about_ca_topic_score_gemma":0.000002701241,"domain_scores_codex":[0.9993044,0.00007039651,0.0001954264,0.0001560443,0.0002043516,0.00006943414],"domain_scores_gemma":[0.9997139,0.00001095773,0.00006049194,0.0001883183,0.00000461187,0.00002173745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002678757,0.0001323181,0.0414388,0.00004665474,0.00002165725,7.205999e-7,0.00103661,0.01418349,0.9414493,0.000001647028,0.00119817,0.0004637979],"study_design_scores_gemma":[0.000650651,0.0001784951,0.1782175,0.0000736115,0.00006692565,0.000001278717,0.000156547,0.03222714,0.7875482,0.000004955572,0.0007238828,0.0001508008],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977809,0.00006430231,0.001060509,0.000643129,0.00007581434,0.0001745078,0.00008964175,0.00001122421,0.0001000172],"genre_scores_gemma":[0.9995045,0.000008317914,0.0003167136,0.00008814238,0.00003377943,0.000002599106,0.00003066856,0.000004493079,0.00001078064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1539011,"threshold_uncertainty_score":0.2865171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03898058251627148,"score_gpt":0.2702173315010007,"score_spread":0.2312367489847293,"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."}}