{"id":"W4393128998","doi":"10.1016/j.compchemeng.2024.108654","title":"Solving least-squares problems in directed networks: A distributed approach","year":2024,"lang":"en","type":"article","venue":"Computers & Chemical Engineering","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Convergence (economics); Focus (optics); Least-squares function approximation; Linear equation; Algebraic number; Algebraic equation; Mathematics; Mathematical optimization; Computer science; Linear system; Exponential function; System of linear equations; Applied mathematics; Nonlinear system; Mathematical analysis","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002928285,0.0003820941,0.0004403651,0.0002329323,0.0000364294,0.0006129662,0.001150294,0.0001699768,0.000001783107],"category_scores_gemma":[0.00007854355,0.0003885858,0.000159161,0.001445747,0.00002750525,0.0005110415,0.0004286166,0.0005378675,0.00001490289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003184148,"about_ca_system_score_gemma":0.00004451212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002649437,"about_ca_topic_score_gemma":4.997949e-7,"domain_scores_codex":[0.9974546,0.00004057315,0.0005456965,0.0008435381,0.0003258383,0.0007897773],"domain_scores_gemma":[0.9988714,0.0002761382,0.00005099738,0.0005351865,0.00004800925,0.0002182953],"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":[0.000003243801,0.000100283,0.0001312625,0.0004013756,0.00009902189,0.0000955569,0.0003740623,0.9722894,0.01251801,0.003620507,0.001181324,0.009185991],"study_design_scores_gemma":[0.0004076898,0.00001208685,0.0002323458,0.0005789455,0.000008660607,0.00004307547,0.000005106618,0.9964623,0.0004265242,0.00003598096,0.001372818,0.0004144677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004424985,0.002027892,0.9892223,0.0001400626,0.001123047,0.0003710168,0.00001165634,0.00260431,0.00007473261],"genre_scores_gemma":[0.9710156,0.000007049076,0.02841397,0.00002588643,0.0002694982,0.000110348,0.0001067412,0.00004175597,0.000009203668],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9665906,"threshold_uncertainty_score":0.9998566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008137832950225474,"score_gpt":0.1909593630060652,"score_spread":0.1828215300558398,"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."}}