{"id":"W2068893578","doi":"10.1021/ma991534r","title":"Using Rheological Data To Determine the Branching Level in Metallocene Polyethylenes","year":2000,"lang":"en","type":"article","venue":"Macromolecules","topic":"Polymer crystallization and properties","field":"Materials Science","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Branching (polymer chemistry); Rheology; Gel permeation chromatography; Molar mass distribution; Polymer; Polymer chemistry; Metallocene; Viscosity; Materials science; Chemistry; Thermodynamics; Polymerization; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003973457,0.0001271457,0.0001551059,0.00004504783,0.0001467717,0.0001339923,0.0007755209,0.00004010572,0.001836929],"category_scores_gemma":[0.00008412361,0.00007976426,0.00002207775,0.0001844248,0.00009704982,0.0001784397,0.0002765269,0.00006575797,0.0001117288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001597412,"about_ca_system_score_gemma":0.0000344796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006107542,"about_ca_topic_score_gemma":0.0002728702,"domain_scores_codex":[0.9988139,0.0001780762,0.0002296738,0.0003197846,0.0001775813,0.0002809906],"domain_scores_gemma":[0.9993424,0.00005049903,0.00003022166,0.0005044847,0.00001285469,0.00005950999],"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":[0.00003883687,0.00002697176,0.0001927058,0.000006194621,0.000003234629,0.00002680004,0.0004481013,0.0005343924,0.9842249,0.0001206324,0.00002573823,0.01435156],"study_design_scores_gemma":[0.0007017459,0.00009384876,0.006443264,0.0001246735,0.00003691366,0.0001658577,0.0003280735,0.02729016,0.9518356,0.000507641,0.01178493,0.0006873297],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939389,0.0007395861,0.003694481,0.0006816789,0.00008429641,0.0001246757,0.00006392512,0.00004510338,0.0006273963],"genre_scores_gemma":[0.9928429,0.00002078838,0.005208192,0.001479024,0.00004539714,0.000005622337,0.00001224862,0.00001315538,0.0003726396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03238927,"threshold_uncertainty_score":0.9990755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2043166370389271,"score_gpt":0.3245085240540233,"score_spread":0.1201918870150963,"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."}}