{"id":"W2170699457","doi":"10.1109/nafips.2006.365854","title":"Predictive Fuzzy Control of Paper Quality","year":2006,"lang":"en","type":"article","venue":"","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Pulp (tooth); Computer science; Monte Carlo method; Chip; Fuzzy logic; Brightness; Process engineering; Data mining; Artificial intelligence; Engineering; Mathematics; Statistics","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":[0.0007501246,0.0005925075,0.0006076153,0.0003743065,0.0003430677,0.00130055,0.0007912133,0.0006810241,0.001406944],"category_scores_gemma":[0.002315301,0.0003385998,0.0003700716,0.0002709611,0.0005908351,0.0004464852,0.0004115186,0.0007642064,0.0002513849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009941147,"about_ca_system_score_gemma":0.0006960287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009835144,"about_ca_topic_score_gemma":0.007347137,"domain_scores_codex":[0.9997422,0.00003974917,0.00001323723,0.00006818624,0.00008906292,0.0000475963],"domain_scores_gemma":[0.9992335,0.0003668299,0.0001297501,0.00004755204,0.0001949379,0.00002740849],"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":[0.0001338664,0.0000759137,0.0004858695,0.00006599486,0.00003099382,0.00005338568,0.00005517154,0.952046,0.007223386,0.002595741,0.0004820105,0.03675166],"study_design_scores_gemma":[0.00001796654,0.00004359796,0.0003214506,0.000005573423,0.000009638748,0.000005789482,0.000005046662,0.9961562,0.001921188,0.001293774,0.0002133882,0.000006413398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1700852,0.0007191647,0.8126804,0.0003816042,0.0001645692,0.0001133679,0.0001699729,0.00106642,0.01461935],"genre_scores_gemma":[0.987142,0.0001075654,0.01131923,0.00003109395,0.00001269557,0.00005131001,0.00004467518,0.000010842,0.001280709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009835144,"threshold_uncertainty_score":0.01955581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01890267728820873,"score_gpt":0.2865037530432375,"score_spread":0.2676010757550288,"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."}}