{"id":"W2207275587","doi":"10.48550/arxiv.2409.11044","title":"Computation and Complexity of Preference Inference Based on Hierarchical Models","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Science Foundation Ireland; Queen's University Belfast","keywords":"Computation; Inference; Preference; Computer science; Artificial intelligence; Theoretical computer science; Mathematics; Algorithm; Statistics","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":[0.00457793,0.0009897876,0.0019826,0.001515108,0.001305635,0.003828559,0.00238016,0.00149495,0.01156684],"category_scores_gemma":[0.0336373,0.001293783,0.002223901,0.002859511,0.001615554,0.008540607,0.003738273,0.00346477,0.0009102075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004271138,"about_ca_system_score_gemma":0.003094198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01873548,"about_ca_topic_score_gemma":0.03214834,"domain_scores_codex":[0.9943922,0.002698914,0.0002932492,0.0008311971,0.001328147,0.0004562492],"domain_scores_gemma":[0.96569,0.03047824,0.0008021757,0.001937231,0.0007665701,0.0003258423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007928585,0.0002870634,0.004341959,0.0006490629,0.0002928072,0.0003707544,0.0005318363,0.6500892,0.001680936,0.1319656,0.008973976,0.200024],"study_design_scores_gemma":[0.00004006288,0.00001336552,0.0002943566,0.00001566729,0.00002631071,0.00002568038,0.00005589395,0.865862,0.0003126686,0.1328765,0.0004652941,0.0000121955],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09750143,0.0006221916,0.8872563,0.002948573,0.00004922591,0.0002753562,0.001434013,0.002135267,0.007777733],"genre_scores_gemma":[0.5536472,0.0004643236,0.438888,0.0004382732,0.000100275,0.0003296295,0.002346602,0.0003146811,0.003471112],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01873548,"threshold_uncertainty_score":0.03869498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1940580369590579,"score_gpt":0.2228332303218106,"score_spread":0.02877519336275269,"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."}}