{"id":"W4415338314","doi":"10.12783/shm2025/37536","title":"Advanced NeRF (ABM-Nerfacto) for High-Definition Digital Twin and Damage Mapping","year":2025,"lang":"","type":"article","venue":"","topic":"Integrated Circuits and Semiconductor Failure Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Deep learning; Bridge (graph theory); Structural health monitoring; Mechanism (biology); Key (lock)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001377987,0.0005040145,0.0006341612,0.0005015294,0.0002339109,0.0006340509,0.0001998183,0.0003164338,0.0004169345],"category_scores_gemma":[0.000132233,0.0004848374,0.0002225511,0.0007272466,0.00007743976,0.0009192336,0.00005614728,0.0003652286,0.00003272476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001543106,"about_ca_system_score_gemma":0.00006619339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001255592,"about_ca_topic_score_gemma":0.00003906042,"domain_scores_codex":[0.9979314,0.00002080665,0.0006871989,0.0006015213,0.0001525519,0.0006064949],"domain_scores_gemma":[0.9989298,0.000247394,0.00008687532,0.000390889,0.0002207957,0.0001242749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001028422,0.0001505383,0.0006468744,0.001472547,0.002981235,0.0000188886,0.0015003,0.008708979,0.3070213,0.3546797,0.00673232,0.3159845],"study_design_scores_gemma":[0.01381299,0.0008649356,0.003162855,0.003373688,0.00341895,0.00002459606,0.02675298,0.3879916,0.1983439,0.1103727,0.2452697,0.006610993],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.735392,0.001969884,0.1708568,0.001076553,0.001312924,0.0008370336,0.0003941596,0.0004134636,0.08774709],"genre_scores_gemma":[0.9905615,0.0003094719,0.001949138,0.0002091076,0.000152411,0.00004789733,0.0002609233,0.00005540484,0.006454076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3792827,"threshold_uncertainty_score":0.9997603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01277194291743227,"score_gpt":0.2136066265540484,"score_spread":0.2008346836366161,"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."}}