{"id":"W4387917265","doi":"10.2139/ssrn.4611603","title":"Yx-Idcrc: Calculating Interdiffusion Coefficients in Completely Miscible Binary Diffusion Systems from Raw Experimental Data","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Mathematical Modeling in Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Binary number; Diffusion; Thermodynamics; Materials science; Raw data; Binary system; Statistical physics; Mathematics; Statistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000755717,0.0006792824,0.0006395354,0.001161716,0.0003099446,0.0009190207,0.001204084,0.001077713,0.002816928],"category_scores_gemma":[0.003169829,0.0003633505,0.0003008033,0.0009421724,0.0003236413,0.0008222441,0.0005961632,0.0007131528,0.0009694618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000502188,"about_ca_system_score_gemma":0.001091159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003992496,"about_ca_topic_score_gemma":0.003195729,"domain_scores_codex":[0.9997829,0.00002910943,0.00001051454,0.00004127243,0.000116708,0.00001962757],"domain_scores_gemma":[0.9992175,0.0003387925,0.00006722824,0.0001559894,0.000185449,0.00003499357],"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":[0.001071409,0.0002615487,0.006523441,0.002018256,0.0002065145,0.0005956033,0.0004150846,0.2563294,0.3920746,0.02952255,0.009129577,0.301852],"study_design_scores_gemma":[0.00003190126,0.00003767583,0.001336405,0.00001129845,0.00001389688,0.0000758975,0.00001761579,0.9187753,0.07613157,0.002515789,0.001025471,0.00002718319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.242626,0.0006264371,0.7289256,0.0001607293,0.0001050845,0.0001941545,0.001958127,0.02190501,0.003498962],"genre_scores_gemma":[0.5600045,0.0003120985,0.4345435,0.00005163452,0.00001625952,0.000276576,0.0009921431,0.001438285,0.002365032],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003992496,"threshold_uncertainty_score":0.009423494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06217097313829819,"score_gpt":0.3155754932202345,"score_spread":0.2534045200819364,"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."}}