{"id":"W2156622941","doi":"10.7939/r3fm9h","title":"Action Elimination and Plan Neighborhood Graph Search: Two Algorithms for Plan Improvement - Extended Version","year":2010,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Satisficing; Plan (archaeology); Computer science; Quality (philosophy); Operations research; Graph; Mathematical optimization; Mathematics; Artificial intelligence; Theoretical computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009912274,0.00009041488,0.00009689942,0.0001599531,0.0002343666,0.00005055451,0.0003366785,0.0000701551,0.0000387203],"category_scores_gemma":[0.000008267912,0.0001013015,0.00004343707,0.0001306138,0.00004518363,0.001246761,0.0001654817,0.0001444914,0.000003660225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007409895,"about_ca_system_score_gemma":0.00006094293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004194886,"about_ca_topic_score_gemma":0.00006255477,"domain_scores_codex":[0.9993551,0.00002546643,0.00007705045,0.0002546318,0.0001256912,0.0001621005],"domain_scores_gemma":[0.9993665,0.0002406168,0.00007561665,0.0001974146,0.00002567351,0.00009413523],"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":[0.001345144,0.000734803,0.02914948,0.000601924,0.0003422216,0.00005638397,0.0405775,0.0007061161,0.0512491,0.2002999,0.02716475,0.6477727],"study_design_scores_gemma":[0.009067193,0.00300042,0.03837464,0.0002472996,0.0001267243,0.00004032136,0.004006621,0.8270777,0.06356142,0.01819234,0.03504511,0.001260169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7721979,0.00003483399,0.2167584,0.004907027,0.0005744219,0.0005085783,0.00003585742,0.0001793126,0.004803701],"genre_scores_gemma":[0.9548824,0.00001973275,0.04380108,0.00009600664,0.0000445775,3.486442e-7,0.0001358226,0.000007782841,0.001012244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8263716,"threshold_uncertainty_score":0.4130955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02018128664592779,"score_gpt":0.2202260040205725,"score_spread":0.2000447173746447,"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."}}