{"id":"W3185905751","doi":"10.1016/j.chroma.2021.462429","title":"Thermal modulation to enhance two-dimensional liquid chromatography separations of polymers","year":2021,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Ministerie van Economische Zaken; Diagnostic Services Manitoba; BASF","keywords":"Chemistry; Polymer; Chromatography; Size-exclusion chromatography; Polystyrene; Analyte; Two-dimensional chromatography; Analytical Chemistry (journal); Gas chromatography; Resolution (logic); Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000234962,0.0003439361,0.0006961198,0.0004378829,0.0001493546,0.00004832635,0.000392507,0.0001962373,0.002324101],"category_scores_gemma":[0.0000794405,0.0003282887,0.001238775,0.001746808,0.0002355336,0.0003095571,0.00008307127,0.0003807802,0.000008326645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000281849,"about_ca_system_score_gemma":0.0002598737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001017709,"about_ca_topic_score_gemma":0.000004161779,"domain_scores_codex":[0.9970154,0.00005877993,0.00126462,0.0003553669,0.0008930136,0.0004127733],"domain_scores_gemma":[0.9973554,0.0001659042,0.0008025915,0.000502211,0.000736166,0.0004377387],"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":[0.0002773623,0.0005083799,0.00294537,0.0001807701,0.0006756512,0.0001013633,0.0002074082,0.002610743,0.9910464,0.0003374157,0.000743979,0.000365178],"study_design_scores_gemma":[0.0007920395,0.0001823553,0.001628605,0.0004354943,0.0002237137,0.0002840535,0.0002309332,0.0003084942,0.9942732,0.000294483,0.0009791536,0.0003674593],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884379,0.001325519,0.0006551163,0.0003168827,0.0001279167,0.00005057436,0.00004532078,0.0000434039,0.008997346],"genre_scores_gemma":[0.9966738,0.00003589489,0.002663624,0.0001868964,0.0002855245,0.000006815802,0.00002699724,0.00003651627,0.00008398987],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008913356,"threshold_uncertainty_score":0.9999169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007696770819620411,"score_gpt":0.2686639696699853,"score_spread":0.260967198850365,"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."}}