{"id":"W4410356880","doi":"10.1145/3672608.3707978","title":"D-semble: Efficient Diversity-Guided Search for Resilient ML Ensembles","year":2025,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diversity (politics); Computer science; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002043118,0.001388316,0.001330739,0.001243504,0.0008929495,0.0008792291,0.001481574,0.001666168,0.001900151],"category_scores_gemma":[0.008232246,0.0006431702,0.001031956,0.000645048,0.0008943136,0.001074216,0.002151682,0.001674041,0.0005747243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008651055,"about_ca_system_score_gemma":0.001318263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002459509,"about_ca_topic_score_gemma":0.005194782,"domain_scores_codex":[0.9990546,0.0003537044,0.00005119389,0.0001847798,0.0002213303,0.0001343531],"domain_scores_gemma":[0.9963086,0.002577534,0.0002098753,0.0003138636,0.0004138648,0.0001761366],"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":[0.0001430226,0.0001515489,0.002816464,0.00005724488,0.0001143595,0.0001176469,0.000146511,0.9004065,0.00399082,0.004159339,0.003193536,0.08470309],"study_design_scores_gemma":[0.00002550801,0.00005895162,0.0001108698,0.000007946213,0.00001320951,0.00002774805,0.00002996703,0.9952241,0.0008273956,0.00321831,0.0004494432,0.00000660525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1577901,0.0008469645,0.8335748,0.0007134434,0.000164206,0.0001695737,0.0002466815,0.002629356,0.00386481],"genre_scores_gemma":[0.7226294,0.0001770223,0.2727572,0.0006056337,0.00008548566,0.0003577182,0.0006297354,0.0003584618,0.002399416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002459509,"threshold_uncertainty_score":0.01080513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03758951799487009,"score_gpt":0.3010328508609558,"score_spread":0.2634433328660857,"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."}}