{"id":"W2080288066","doi":"10.1002/pc.20077","title":"Comprehensive thermal optimization of liquid composite molding to reduce cycle time and processing stresses","year":2005,"lang":"en","type":"article","venue":"Polymer Composites","topic":"Epoxy Resin Curing Processes","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Massachusetts Institute of Technology","keywords":"Materials science; Thermosetting polymer; Composite number; Composite material; Molding (decorative); Curing (chemistry); Residual stress; Viscoelasticity; Image stitching; Computer science","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":[0.0003163084,0.0005448234,0.0003748394,0.0003956717,0.0001999115,0.000333255,0.0002502347,0.0002585242,0.0006825579],"category_scores_gemma":[0.0004335652,0.0002267578,0.0002539517,0.0002096151,0.0002140146,0.0002284544,0.0002697951,0.0001953546,0.0001095554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003674671,"about_ca_system_score_gemma":0.000473887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009510253,"about_ca_topic_score_gemma":0.00183558,"domain_scores_codex":[0.9998848,0.00002301139,0.000004513352,0.00002158062,0.00004322951,0.00002276478],"domain_scores_gemma":[0.9998337,0.00005683118,0.00004194019,0.00001599585,0.00003781948,0.00001370112],"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":[0.00006181094,0.00008723959,0.0004961709,0.00004363417,0.0000158516,0.00002466685,0.00003368127,0.9150544,0.05519516,0.0007721385,0.0001694797,0.02804588],"study_design_scores_gemma":[0.00001511589,0.0001220336,0.0005407762,0.000003285239,0.0000148259,0.00001097984,0.000008610302,0.982254,0.0163448,0.0002844214,0.000396188,0.000004976802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.680542,0.0003344037,0.3136908,0.00005589374,0.00001668436,0.00006740158,0.00003654662,0.0004848639,0.004771513],"genre_scores_gemma":[0.9652916,0.00005030823,0.03364854,0.000007159211,0.00000266046,0.00003691245,0.00003194311,0.00003787229,0.0008930395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009510253,"threshold_uncertainty_score":0.002666116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008578437969484088,"score_gpt":0.2321487071108516,"score_spread":0.2235702691413675,"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."}}