{"id":"W4416004471","doi":"10.1145/3731599.3767347","title":"ROSE: RADICAL Orchestrator for Surrogate Exploration","year":2025,"lang":"","type":"article","venue":"","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Orchestration; Scalability; Asynchronous communication; Surrogate model; Throughput; Software; Inference","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":[0.002756606,0.001877908,0.001149633,0.0007210352,0.000662039,0.001923119,0.003782441,0.001104585,0.01723953],"category_scores_gemma":[0.005767488,0.0009632275,0.001766421,0.000620666,0.001215254,0.002818345,0.005131408,0.002928783,0.008341334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006774647,"about_ca_system_score_gemma":0.00161482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001567204,"about_ca_topic_score_gemma":0.002323847,"domain_scores_codex":[0.9982188,0.0004460388,0.0001479637,0.0004040457,0.00057515,0.0002080022],"domain_scores_gemma":[0.9982693,0.0005733403,0.00008789804,0.0006374325,0.0002238446,0.0002080968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003920561,0.0007049644,0.007104319,0.001817988,0.0005545839,0.001345986,0.001789311,0.1882455,0.08960024,0.1156695,0.2040731,0.3851741],"study_design_scores_gemma":[0.0003838463,0.0002463025,0.0006842181,0.0001024474,0.00006720969,0.0002633522,0.0001360361,0.7254914,0.05025828,0.04038737,0.1818113,0.0001682789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007084699,0.0003595725,0.784041,0.0002528859,0.0001805556,0.0002764933,0.00106715,0.1971164,0.009621178],"genre_scores_gemma":[0.2172832,0.0009594083,0.7010602,0.0009982549,0.0001473092,0.001621471,0.01124717,0.0486891,0.01799382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01723953,"threshold_uncertainty_score":0.05767202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02903142424395828,"score_gpt":0.3319663657140954,"score_spread":0.3029349414701372,"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."}}