{"id":"W2211274022","doi":"10.1609/icaps.v24i1.13640","title":"The Complexity of Partial-Order Plan Viability Problems","year":2014,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Automated Planning and Scheduling","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ottawa","keywords":"Heuristics; Plan (archaeology); Order (exchange); Computer science; Task (project management); Management science; Mathematical optimization; Mathematics; Engineering; Economics; Systems engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001316474,0.0001498962,0.000192387,0.0000642337,0.0003329027,0.0002460819,0.001242044,0.00006893693,0.000003956322],"category_scores_gemma":[0.0005570092,0.00009418943,0.00005003866,0.0001908284,0.0002860516,0.0001924707,0.0002665735,0.0002718698,0.000001637127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001801501,"about_ca_system_score_gemma":0.00005753437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004141812,"about_ca_topic_score_gemma":0.000001203354,"domain_scores_codex":[0.9986306,0.0000330787,0.0003968949,0.0002870178,0.0004412933,0.0002110851],"domain_scores_gemma":[0.9985509,0.000294387,0.0004543636,0.0001594973,0.0004874384,0.00005340497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008598603,0.00007723246,0.05406874,0.0001644012,0.00010933,3.362547e-7,0.002909924,0.009654334,0.01710879,0.9126765,0.0003082835,0.00283619],"study_design_scores_gemma":[0.0002109492,0.00008224065,0.005172887,0.0005353081,0.000007065161,0.000007322374,0.0001557692,0.9620799,0.01009833,0.02129941,0.0002324883,0.0001183078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675087,0.00007965317,0.01237285,0.007751788,0.0005325883,0.0002536686,0.00001094089,0.0003957876,0.01109407],"genre_scores_gemma":[0.9891952,0.000005140647,0.0106157,0.00009058836,0.00003141589,0.00000870824,0.000002332183,0.000006177977,0.00004468972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9524256,"threshold_uncertainty_score":0.3840933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06234092099937335,"score_gpt":0.2806450439406484,"score_spread":0.2183041229412751,"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."}}