{"id":"W4327667135","doi":"10.48550/arxiv.2303.08229","title":"Sensor network design for post-combustion CO2 capture plants: economy, complexity and robustness","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Observability; Robustness (evolution); Computer science; Sensitivity (control systems); Optimization problem; Mathematical optimization; Wireless sensor network; Fault tolerance; Redundancy (engineering); Real-time computing; Control theory (sociology); Distributed computing; Engineering; Algorithm; Mathematics; Control (management); Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009650178,0.000920353,0.0007343647,0.0003229654,0.000415202,0.0007772527,0.0009603034,0.0009113602,0.001425835],"category_scores_gemma":[0.00241321,0.000410494,0.0005101755,0.0003965053,0.0007031407,0.001252917,0.0009862276,0.001070236,0.0002070278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001314,"about_ca_system_score_gemma":0.0008486935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001750351,"about_ca_topic_score_gemma":0.002124805,"domain_scores_codex":[0.9993612,0.0002258965,0.0000242096,0.0001468645,0.0001849114,0.00005694405],"domain_scores_gemma":[0.9990613,0.0005882662,0.000125322,0.00005418638,0.0001469382,0.0000240128],"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":[0.00004441677,0.00001667918,0.000223923,0.0001042822,0.00001806617,0.00004196458,0.00002631019,0.9705126,0.005817221,0.007469318,0.0002969068,0.01542839],"study_design_scores_gemma":[0.000005067665,0.00002952848,0.00009908547,0.000006027087,0.000005304226,0.00001620037,0.000009680395,0.9933223,0.00178642,0.004293125,0.0004231208,0.000004029936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01200989,0.0004409498,0.9851579,0.0002844619,0.00003060658,0.00005282501,0.00003739751,0.00009304578,0.00189297],"genre_scores_gemma":[0.8495626,0.001138034,0.1456385,0.000121053,0.00006991483,0.0002602531,0.0001090596,0.00005399442,0.003046626],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001750351,"threshold_uncertainty_score":0.007265091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1163116046475528,"score_gpt":0.1984659980087692,"score_spread":0.08215439336121642,"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."}}