{"id":"W2258482718","doi":"10.4271/2005-01-1520","title":"Advanced In-cycle and Cycle-to Cycle On-line Adaptive Control for Thermoforming of Large Thermoplastic Sheets","year":2005,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; National Research Council Canada","funders":"","keywords":"Thermoforming; Thermoplastic; Materials science; Line (geometry); Mechanical engineering; Control theory (sociology); Computer science; Composite material; Control (management); Engineering; Mathematics; 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":[0.0001879432,0.0002320065,0.0001817107,0.0001463067,0.0001791034,0.0002831352,0.0004767717,0.0001729598,0.002057496],"category_scores_gemma":[0.0003196504,0.00009255599,0.0001127424,0.00009754307,0.0001947212,0.0001901058,0.0002057711,0.0002614445,0.000213655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001979885,"about_ca_system_score_gemma":0.0001572279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000935717,"about_ca_topic_score_gemma":0.00183671,"domain_scores_codex":[0.9998778,0.00002589031,0.000006287206,0.00002631272,0.00005290863,0.00001077607],"domain_scores_gemma":[0.9998318,0.00004737965,0.00002476997,0.00003861078,0.00004667171,0.00001071323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006801157,0.0003811298,0.00169386,0.0001938159,0.00005380844,0.0001356969,0.0004043047,0.1950611,0.3514252,0.004218708,0.002789766,0.4429625],"study_design_scores_gemma":[0.00003614412,0.0002971823,0.001256577,0.00000637897,0.00001319785,0.00006514503,0.0000139625,0.9326206,0.05973018,0.0009905836,0.004951665,0.00001837349],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2670225,0.000195481,0.7212062,0.0001136063,0.0001152795,0.00009831805,0.00007142463,0.002856796,0.008320394],"genre_scores_gemma":[0.9682775,0.00003803729,0.0292789,0.00003173943,0.000015108,0.00003567104,0.00003036076,0.00004348903,0.002249265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002057496,"threshold_uncertainty_score":0.006883025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007442865761558718,"score_gpt":0.2465208521926052,"score_spread":0.2390779864310464,"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."}}