{"id":"W2013253797","doi":"10.1016/j.engappai.2010.06.012","title":"A comparison of two data analysis techniques and their applications for modeling the carbon dioxide capture process","year":2010,"lang":"en","type":"article","venue":"Engineering Applications of Artificial Intelligence","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Canada Research Chairs","keywords":"Computer science; Process (computing); Carbon dioxide; Process engineering; Data mining; Programming language","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":[0.00605398,0.001177829,0.001430082,0.003486793,0.0006396131,0.002253877,0.001275177,0.001587477,0.001291076],"category_scores_gemma":[0.02018967,0.0003754756,0.001819921,0.002574573,0.0005425339,0.00243135,0.001277928,0.001400328,0.0003409128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009162203,"about_ca_system_score_gemma":0.001462643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008964761,"about_ca_topic_score_gemma":0.005263411,"domain_scores_codex":[0.9973282,0.001175847,0.0002344746,0.0003469936,0.0007951456,0.0001193463],"domain_scores_gemma":[0.9816787,0.01463971,0.0006283572,0.001027365,0.00189523,0.0001306953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002773061,0.001078567,0.03094316,0.0009430118,0.001007998,0.0002344978,0.0007701253,0.2504791,0.01665819,0.02316732,0.001714362,0.6702305],"study_design_scores_gemma":[0.00007999786,0.0003620011,0.005856636,0.00004465556,0.0001552853,0.00009421567,0.0001628837,0.9799713,0.007162074,0.004563804,0.001496096,0.00005104281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08176091,0.0006046495,0.9138966,0.0004406418,0.00007748021,0.0002408007,0.0004019963,0.001082584,0.001494264],"genre_scores_gemma":[0.4220425,0.0008584866,0.5746744,0.0001201676,0.00006493476,0.0004224648,0.0006490202,0.0001862979,0.00098174],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008964761,"threshold_uncertainty_score":0.03201693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03617838724407821,"score_gpt":0.3235821207633919,"score_spread":0.2874037335193137,"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."}}