{"id":"W2159458393","doi":"10.1002/masy.201400202","title":"Effect of Column Type on Polyolefin Fractionation by High‐Temperature Thermal Gradient Interaction Chromatography","year":2015,"lang":"en","type":"article","venue":"Macromolecular Symposia","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Waterloo","funders":"","keywords":"Comonomer; Polyolefin; Fractionation; Materials science; Chromatography; Crystallization; Copolymer; Particle (ecology); Octene; Chemical engineering; Chemistry; Polymer; Composite material; Organic chemistry","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":[0.000781213,0.0007987102,0.0005919873,0.0005478569,0.0002723942,0.001060312,0.0004936341,0.0005757422,0.002587911],"category_scores_gemma":[0.001613433,0.0004929989,0.000354281,0.0005956219,0.0003194584,0.0004787251,0.0002822339,0.0006364392,0.001115781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002785364,"about_ca_system_score_gemma":0.0003054838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008690262,"about_ca_topic_score_gemma":0.001020822,"domain_scores_codex":[0.9990746,0.0002063275,0.0001193936,0.0002202844,0.0001988785,0.0001805202],"domain_scores_gemma":[0.9982314,0.001131666,0.0001358723,0.0001163034,0.0002408929,0.0001439349],"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":[0.0006589389,0.0001224569,0.0005140668,0.00008272519,0.00003439349,0.00003884524,0.00001692196,0.000126967,0.9957063,0.00002119069,0.0001074334,0.002569806],"study_design_scores_gemma":[0.00002430535,0.0002936832,0.002929738,0.000006529916,0.0000641655,0.00007475646,0.00001173294,0.0006888146,0.9950847,0.00000985113,0.0007999443,0.00001179125],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832588,0.003313032,0.008652062,0.000192342,0.0002937751,0.0001772088,0.0007307404,0.0005692426,0.002812726],"genre_scores_gemma":[0.9732563,0.002389041,0.01819389,0.0006104678,0.0001154626,0.0002354172,0.00168259,0.0005628234,0.002953988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002587911,"threshold_uncertainty_score":0.008657455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003893116332772461,"score_gpt":0.229073239619016,"score_spread":0.2251801232862436,"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."}}