{"id":"W4416541551","doi":"10.48550/arxiv.2504.11835","title":"Particle Data Cloning for Complex Ordinary Differential Equations","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Simon Fraser University","keywords":"Ode; Ordinary differential equation; Frequentist inference; Particle filter; Inference; Cloning (programming); Statistical inference; Global optimization","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003981219,0.001015534,0.001419438,0.0009986593,0.00102388,0.00154033,0.002191802,0.001968154,0.003695349],"category_scores_gemma":[0.01915538,0.001060323,0.001554785,0.001115325,0.00223312,0.00191783,0.002946135,0.002928908,0.0007978597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001966493,"about_ca_system_score_gemma":0.002259327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008562649,"about_ca_topic_score_gemma":0.005906971,"domain_scores_codex":[0.9985477,0.0006001118,0.00008409849,0.0002776829,0.0004108728,0.00007946293],"domain_scores_gemma":[0.9909889,0.006570024,0.0005703627,0.0008737596,0.0007846453,0.0002123706],"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":[0.0000785659,0.0000446992,0.00174037,0.0001682064,0.0000603176,0.0001597161,0.0001608568,0.752601,0.001863909,0.2027409,0.001575425,0.03880607],"study_design_scores_gemma":[0.00001092393,0.000008721717,0.00007170134,0.00001010493,0.000005223455,0.00001442282,0.000005328825,0.9733183,0.0004337468,0.02512169,0.0009919752,0.000007823272],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001954109,0.0001067672,0.9970782,0.0001028327,0.0000284351,0.00002453106,0.00003101147,0.0001399355,0.0005342608],"genre_scores_gemma":[0.2605022,0.0006866804,0.7327464,0.0003779313,0.000133496,0.0005859237,0.0004375267,0.0004373811,0.004092293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008562649,"threshold_uncertainty_score":0.02105492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2105553698004423,"score_gpt":0.3585128331703055,"score_spread":0.1479574633698632,"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."}}