{"id":"W4412877242","doi":"10.1145/3711896.3736999","title":"Hyperparametric Influence Minimization: Feature-Driven Intervention Beyond Blocking","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Research Foundation","keywords":"Blocking (statistics); Minification; Computer science; Feature (linguistics); Intervention (counseling); Computer network; Psychology; World Wide Web","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":[0.003175518,0.001220428,0.001977979,0.0006877627,0.0005797139,0.001669199,0.002642116,0.001959947,0.002440464],"category_scores_gemma":[0.01500356,0.0008317977,0.001089362,0.0007579976,0.002633303,0.002915842,0.002680712,0.00227561,0.0004249081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001356394,"about_ca_system_score_gemma":0.001170032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00190047,"about_ca_topic_score_gemma":0.001558603,"domain_scores_codex":[0.998164,0.0008946873,0.000065154,0.0004380006,0.0002858971,0.000152232],"domain_scores_gemma":[0.9906735,0.007113691,0.00090864,0.0006415903,0.000380731,0.0002817879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000124725,0.00007202128,0.001296442,0.0001777788,0.000105314,0.000185935,0.0001810482,0.8026338,0.00502791,0.1623285,0.001447456,0.02641896],"study_design_scores_gemma":[0.00001171064,0.00003054037,0.0001394176,0.00001082164,0.00001537026,0.00003750387,0.00001306931,0.9546677,0.0009469037,0.04349183,0.0006244387,0.00001072819],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01239324,0.0002073253,0.9857862,0.0002815467,0.00001422283,0.0000296195,0.0000385062,0.00009187563,0.001157361],"genre_scores_gemma":[0.8111703,0.0006359498,0.1809575,0.0005256866,0.0001461434,0.000416423,0.0002075423,0.0002727306,0.005667775],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003175518,"threshold_uncertainty_score":0.01679391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006252236179735615,"score_gpt":0.2571757392529401,"score_spread":0.2509235030732044,"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."}}