{"id":"W2523048607","doi":"10.1002/aic.15511","title":"Input–output pairing accounting for both structure and strength in coupling","year":2016,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pairing; Closeness; Measure (data warehouse); Sensitivity (control systems); Computer science; Topology (electrical circuits); Matrix (chemical analysis); Coupling strength; Coupling (piping); Degree (music); Network topology; Physical system; Control theory (sociology); Mathematics; Algorithm; Data mining; Control (management); Engineering; Artificial intelligence; Electronic engineering; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002454156,0.0001071714,0.0001457115,0.00007951608,0.00006268879,0.00008087968,0.00006697591,0.0001094947,0.00004055877],"category_scores_gemma":[0.00003835844,0.00006892032,0.00002673616,0.0000435963,0.00001259748,0.0001762316,0.00001910275,0.0001660344,0.000001615799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004441526,"about_ca_system_score_gemma":0.00001224975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002368041,"about_ca_topic_score_gemma":0.000005333908,"domain_scores_codex":[0.9993663,0.000005610303,0.000233195,0.0000837903,0.00007187267,0.0002392123],"domain_scores_gemma":[0.9997386,0.00008011526,0.00004907054,0.00005730215,0.00002014928,0.00005475426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009056166,0.00003115671,0.02760151,0.001404914,0.0002773302,0.00007952668,0.001301745,0.08576804,0.8288637,0.0001316373,0.003301137,0.05114878],"study_design_scores_gemma":[0.02610807,0.0005850794,0.0690704,0.008095181,0.0004056025,0.001877228,0.001400919,0.366265,0.3910134,0.02188699,0.108999,0.004293082],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996216,0.00194172,0.0008381779,0.0000853741,0.0006304365,0.00006805471,0.000008004434,0.00004327784,0.0001689531],"genre_scores_gemma":[0.9969004,0.001278424,0.001361009,0.00001784391,0.0003623635,0.00000141995,6.384341e-7,0.00002900304,0.00004886841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4378503,"threshold_uncertainty_score":0.2810489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007046092062817648,"score_gpt":0.2000732602011098,"score_spread":0.1930271681382921,"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."}}