{"id":"W4417041447","doi":"10.48550/arxiv.2504.19989","title":"HJRNO: Hamilton-Jacobi Reachability with Neural Operators","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Reachability; Generalization; Obstacle; Artificial neural network; Inference; Hybrid system","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0009039748,0.0006475648,0.0007061615,0.0002230935,0.0004124338,0.0002782671,0.003412489,0.000421643,0.00003410275],"category_scores_gemma":[0.0004138575,0.0005609081,0.0002121714,0.0006303505,0.0002211661,0.0004814656,0.004220522,0.002947969,0.00006289707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002666895,"about_ca_system_score_gemma":0.0005719173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007262033,"about_ca_topic_score_gemma":0.00008452387,"domain_scores_codex":[0.9958158,0.0006096428,0.0005620786,0.001816072,0.0005521452,0.0006442593],"domain_scores_gemma":[0.9959239,0.0003542997,0.0003273179,0.00293182,0.0002666055,0.0001960406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005162619,0.0001444942,0.8184399,0.0003081702,0.0001697046,0.0001300495,0.002679939,0.1663661,0.00008152752,0.003193273,0.0004547691,0.007980463],"study_design_scores_gemma":[0.001835572,0.0003530122,0.5333536,0.0009221003,0.0001887073,0.00004419844,0.0002053336,0.4461411,0.001089278,0.001630534,0.01142817,0.002808366],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.711044,0.0001447964,0.2794206,0.001567318,0.00248929,0.0005945142,0.00001132365,0.0007719211,0.003956307],"genre_scores_gemma":[0.9664812,0.00001730417,0.03039056,0.0007314844,0.0003300194,0.00009185982,0.00002608637,0.0000373249,0.001894164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2850863,"threshold_uncertainty_score":0.9996842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02592189454220674,"score_gpt":0.2802650962406976,"score_spread":0.2543432016984909,"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."}}