{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003873118,0.0007567292,0.001695845,0.00136133,0.001494813,0.005203041,0.002314153,0.001955424,0.004918922],"category_scores_gemma":[0.04464605,0.0008040695,0.001701844,0.002223333,0.002735356,0.008098107,0.003243343,0.003494505,0.0004133273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002776731,"about_ca_system_score_gemma":0.002600308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00601256,"about_ca_topic_score_gemma":0.004990572,"domain_scores_codex":[0.9951864,0.001866132,0.0003408729,0.0007343794,0.001412801,0.000459502],"domain_scores_gemma":[0.9451975,0.04889434,0.002326288,0.001553428,0.001268396,0.0007600116],"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":[0.0003078293,0.0001760288,0.005158874,0.0004947956,0.0001382922,0.0003382417,0.0008011928,0.6936076,0.001115301,0.2382172,0.004785282,0.05485928],"study_design_scores_gemma":[0.00006225641,0.00003976127,0.001012692,0.0000523259,0.00003964276,0.0001355234,0.0003062967,0.5306145,0.0006392163,0.4649875,0.002083266,0.0000270368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3731991,0.002251467,0.5830362,0.01241406,0.0001118523,0.0004833053,0.002821041,0.0009486983,0.02473425],"genre_scores_gemma":[0.8553382,0.001400489,0.1364361,0.0003336743,0.0001751991,0.0005416355,0.002165518,0.0002454021,0.00336377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00601256,"threshold_uncertainty_score":0.02048331,"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."}}