{"id":"W2800683527","doi":"10.1002/mren.201700066","title":"Mapping the Structure–Property Space of Bimodal Polyethylenes Using Response Surface Methods. Part 1: Digital Data Investigation","year":2018,"lang":"en","type":"article","venue":"Macromolecular Reaction Engineering","topic":"Polymer crystallization and properties","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Branching (polymer chemistry); Polymer; Polymerization; Materials science; Polymer architecture; Molar mass distribution; Kinetic chain length; Biological system; Copolymer; Polymer chemistry; Radical polymerization; Composite material","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":[0.000597492,0.0003143394,0.00026477,0.0008944439,0.000117534,0.0004538673,0.0002828487,0.0002662636,0.001275693],"category_scores_gemma":[0.001330103,0.0001585967,0.0002973883,0.0004216338,0.0003985744,0.0005129786,0.0003084019,0.0003320846,0.0001872449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002966707,"about_ca_system_score_gemma":0.0002064055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002767552,"about_ca_topic_score_gemma":0.0002356819,"domain_scores_codex":[0.9998164,0.00004256413,0.0000100218,0.00003631801,0.00007804538,0.00001669637],"domain_scores_gemma":[0.9993603,0.0003287142,0.00008024128,0.0001421656,0.00007147481,0.00001710703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002047171,0.000177786,0.003260038,0.0001853153,0.00003158938,0.00007001583,0.00009528347,0.03398404,0.8472782,0.00505252,0.0002429203,0.1094174],"study_design_scores_gemma":[0.00001975838,0.000239942,0.006569323,0.000006226033,0.00001599729,0.0001415435,0.00006742539,0.5270572,0.45976,0.004175559,0.001910166,0.00003677469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3805269,0.0002070577,0.6163927,0.0001021309,0.00001127428,0.00007274316,0.0003334558,0.0009697387,0.00138395],"genre_scores_gemma":[0.8225885,0.0001531688,0.1760653,0.00002898518,0.000005918672,0.0001175201,0.0003257304,0.00004769033,0.000667238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001275693,"threshold_uncertainty_score":0.004267573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06165925944052748,"score_gpt":0.2783844677546614,"score_spread":0.2167252083141339,"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."}}