{"id":"W4248988076","doi":"10.32920/ryerson.14647389","title":"Experimental Investigation of Thermal Diffusion in Binary and Ternary Hydrocarbon Mixtures","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Field-Flow Fractionation Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency","keywords":"Ternary operation; Thermophoresis; Diffusion; Temperature gradient; Thermal; Thermodynamics; Materials science; Binary number; Thermal diffusivity; Hydrocarbon mixtures; Hydrocarbon; Convection; Interferometry; Mechanics; Analytical Chemistry (journal); Chemistry; Optics; Chromatography; Physics; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004160482,0.0003218511,0.000473044,0.0003405186,0.0005708759,0.0003190068,0.0003898463,0.0005237192,0.001322828],"category_scores_gemma":[0.0008714873,0.0002058751,0.0002261571,0.0005858587,0.0005347054,0.0005111093,0.0005848915,0.0006409398,0.0001755744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002926122,"about_ca_system_score_gemma":0.0003168825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001065315,"about_ca_topic_score_gemma":0.0008976998,"domain_scores_codex":[0.9995321,0.00004422657,0.00003266061,0.00009723987,0.0002239478,0.00006986387],"domain_scores_gemma":[0.9995642,0.0001295211,0.00009057771,0.00004711207,0.0001336194,0.00003498655],"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":[0.0004210058,0.0001500802,0.001668952,0.0002331238,0.00001040707,0.0001383592,0.0001872472,0.005834844,0.9857078,0.001304052,0.0001859822,0.004158103],"study_design_scores_gemma":[0.00004011691,0.0005360572,0.002516821,0.0000157718,0.00002092882,0.00009769541,0.0001297223,0.03556383,0.9594737,0.0002770367,0.001299088,0.00002923713],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925373,0.0004450691,0.005186884,0.00007777774,0.00002391586,0.00002933968,0.000167746,0.00007132333,0.001460507],"genre_scores_gemma":[0.9935689,0.0002729463,0.005228963,0.00002373622,0.000007878457,0.00004777526,0.00008904703,0.00001365954,0.0007469923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001322828,"threshold_uncertainty_score":0.004425347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009708674267992132,"score_gpt":0.2270939252696943,"score_spread":0.2173852510017022,"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."}}