{"id":"W45766481","doi":"","title":"Efficient ADD operations for point-based algorithms","year":2008,"lang":"en","type":"article","venue":"International Conference on Automated Planning and Scheduling","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Scalability; Representation (politics); Locality; Point (geometry); Reachability; Algorithm; Set (abstract data type); State (computer science); Set operations; State space; Current (fluid); Theoretical computer science; Backup; Mathematical optimization; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003789508,0.0001307779,0.0001188531,0.0001947282,0.0003211692,0.0001847784,0.0004288948,0.00007034414,0.0000149664],"category_scores_gemma":[0.0002674946,0.0001257416,0.00003857649,0.0001285151,0.00005344624,0.0001502658,0.00004558666,0.0001353554,0.00001522922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004251767,"about_ca_system_score_gemma":0.0001218308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009569053,"about_ca_topic_score_gemma":3.960756e-7,"domain_scores_codex":[0.9989168,0.00005150713,0.0002477613,0.0003363951,0.00026806,0.0001794521],"domain_scores_gemma":[0.9992356,0.0001302781,0.0000755695,0.0001944202,0.0002903756,0.00007371644],"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":[0.0000469344,0.0001039588,0.000292803,0.00001329941,0.00003507284,0.0000177155,0.001298402,0.6997483,0.003211226,0.2909789,0.0001558193,0.004097558],"study_design_scores_gemma":[0.0004487349,0.00008863267,0.00111725,0.00009851054,0.00000268113,0.00003159655,0.00006989132,0.9948984,0.002813167,0.0001926282,0.0000878847,0.0001506566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1319119,0.00002690933,0.8648109,0.0006391821,0.0005692799,0.0001533781,0.00001663564,0.0005951311,0.001276711],"genre_scores_gemma":[0.5384413,0.000001591116,0.4612396,0.0001836375,0.00003343989,0.00003231556,0.00002180008,0.000004914827,0.00004137706],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4065295,"threshold_uncertainty_score":0.5127593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1006869758632335,"score_gpt":0.3620534760597721,"score_spread":0.2613665001965386,"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."}}