{"id":"W2386299137","doi":"","title":"A Dual Causs-Sedel Iteration Method in Calculation of Cost Tree of Power Project Budget","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Smart Grid and Power Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Convergence (economics); Tree (set theory); Mathematical optimization; Dual (grammatical number); Power (physics); Power iteration; Tree structure; Node (physics); Iterative method; Algorithm; Binary tree; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001345599,0.0001064101,0.000185909,0.0001938007,0.00001854054,0.00001409603,0.00008065692,0.00007016239,0.000003569199],"category_scores_gemma":[3.064847e-7,0.0001108862,0.00005178533,0.0003717219,0.0000141995,0.00007239754,0.00001555267,0.00006307202,0.000006425325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004262043,"about_ca_system_score_gemma":0.00001907376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002355143,"about_ca_topic_score_gemma":0.0001489166,"domain_scores_codex":[0.9991982,0.0000301318,0.0004397961,0.0001269659,0.00008636604,0.0001185458],"domain_scores_gemma":[0.9996218,0.00004789224,0.00007122886,0.0001810234,0.00006302389,0.00001501272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002303765,0.0005709249,0.02543837,0.0006226498,0.0001095852,0.000002250464,0.005686697,0.1569096,0.7056974,0.0115445,0.05506783,0.03832708],"study_design_scores_gemma":[0.001811497,0.00006400266,0.1277301,0.0001365149,0.00004136642,0.00004305163,0.00009982641,0.1340356,0.1331882,0.0002190732,0.6020324,0.0005982811],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06302804,0.0001203551,0.9336376,0.00002346402,0.0000890587,0.000987748,0.00004849464,0.00007097822,0.001994222],"genre_scores_gemma":[0.9140785,0.000002663345,0.08487919,0.00001265264,0.0003352232,0.000397827,0.0001933721,0.00002503565,0.00007555074],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8510504,"threshold_uncertainty_score":0.4521808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00757253331644971,"score_gpt":0.2517597863876344,"score_spread":0.2441872530711847,"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."}}