{"id":"W1967576426","doi":"10.1088/0953-8984/22/3/035105","title":"A molecular dynamics simulation of the diffusion of the solute (Au) and the self-diffusion of the solvent (Cu) in a very dilute liquid Cu–Au solution","year":2009,"lang":"en","type":"article","venue":"Journal of Physics Condensed Matter","topic":"nanoparticles nucleation surface interactions","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Queen's University","funders":"","keywords":"Diffusion; Molecular dynamics; Work (physics); Thermodynamics; Solvent; Constant (computer programming); Fick's laws of diffusion; Effective diffusion coefficient; Atmospheric temperature range; Chemistry; Chemical physics; Range (aeronautics); Molecular diffusion; Self-diffusion; Materials science; Physical chemistry; Computational chemistry; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003770672,0.0001007407,0.0002051114,0.00003949142,0.000132613,0.00001780581,0.0002630347,0.00004501701,0.00003067949],"category_scores_gemma":[0.00004375188,0.00004762974,0.0001995673,0.0002459751,0.0001937336,0.0001974392,0.00004840448,0.0002329857,0.000002182686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004456524,"about_ca_system_score_gemma":0.0001359605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003627391,"about_ca_topic_score_gemma":0.0004772097,"domain_scores_codex":[0.9985543,0.0002870641,0.0005084987,0.00008475585,0.0004287959,0.0001365265],"domain_scores_gemma":[0.9985079,0.0002368445,0.0008259917,0.000254696,0.0001479472,0.00002667314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001121505,0.000421957,0.185774,0.00006277335,0.0001099603,0.000001769816,0.008479861,0.3398354,0.4611803,0.0003351124,0.0001327186,0.002544754],"study_design_scores_gemma":[0.001290604,0.0001516298,0.6656041,0.0002077421,0.0001085438,0.00001296884,0.0003096548,0.3100842,0.01946862,0.002660382,0.0000250477,0.00007652715],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948634,0.00003540856,0.0005748947,0.003937412,0.0002651151,0.0002210437,0.00001329795,0.000002260525,0.00008720303],"genre_scores_gemma":[0.9994741,0.000009164586,0.00005027939,0.0004053015,0.00003545837,2.53572e-7,9.741402e-7,0.000003825809,0.00002065967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4798301,"threshold_uncertainty_score":0.1942284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007231858497782157,"score_gpt":0.2164160508102271,"score_spread":0.209184192312445,"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."}}