{"id":"W2971729282","doi":"10.1002/aic.16784","title":"Modeling of sequence length distribution for olefin copolymerization with vanadium‐based catalyst","year":2019,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Polymer crystallization and properties","field":"Materials Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Polyolefin; Vanadium; Olefin fiber; Sequence (biology); Molar mass distribution; Catalysis; Polymer; Copolymer; Materials science; Thermodynamics; Methylene; Mole fraction; Polymer chemistry; Chemistry; Organic chemistry; Composite material; Physics","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":[0.0001971606,0.0003198991,0.000229382,0.0002816737,0.0001176003,0.0002303799,0.0003009507,0.0004353972,0.0003891846],"category_scores_gemma":[0.000431891,0.0001990563,0.0002913217,0.0002261364,0.0001661668,0.0002892951,0.0001187078,0.0002241516,0.0001255622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007150171,"about_ca_system_score_gemma":0.000373892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005330666,"about_ca_topic_score_gemma":0.002508969,"domain_scores_codex":[0.9999399,0.000009376348,0.000002906874,0.00001916253,0.00001764022,0.0000109961],"domain_scores_gemma":[0.9998515,0.00008583843,0.00002509804,0.000009012721,0.00002111478,0.000007388584],"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":[0.00005551723,0.00002310016,0.0008819255,0.00002660889,0.000006424949,0.00003688847,0.00001054315,0.9575263,0.03867051,0.0005614363,0.00003169781,0.002169078],"study_design_scores_gemma":[0.000001626664,0.000009522038,0.0001250915,7.211523e-7,9.197282e-7,0.000002459568,0.000001420776,0.9923736,0.007380934,0.00004820367,0.00005379934,0.000001644524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271666,0.0002375894,0.07001656,0.00006507728,0.000009145586,0.00002751677,0.0002155258,0.000145235,0.002116851],"genre_scores_gemma":[0.9957912,0.0001013183,0.003222725,0.000004696896,0.000001068301,0.00002180857,0.00008703503,0.00001185726,0.0007581617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005330666,"threshold_uncertainty_score":0.01059926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02509430139927611,"score_gpt":0.2437660241220709,"score_spread":0.2186717227227948,"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."}}