{"id":"W2945253606","doi":"10.1080/14786435.2019.1615149","title":"Influence of variable diffusion coefficient on solid-liquid interface migration kinetics during transient liquid phase bonding","year":2019,"lang":"en","type":"article","venue":"The Philosophical Magazine A Journal of Theoretical Experimental and Applied Physics","topic":"Electronic Packaging and Soldering Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion; Isothermal process; Thermodynamics; Thermal diffusivity; Materials science; Transient (computer programming); Discretization; Phase (matter); Standard deviation; Displacement (psychology); Constant (computer programming); Fick's laws of diffusion; Kinetics; Mechanics; Statistical physics; Mathematics; Chemistry; Mathematical analysis; Physics; Classical mechanics; Statistics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001394562,0.0001992083,0.0003269864,0.00004835848,0.00005360914,0.00001813666,0.0002374,0.00007419344,0.0000105788],"category_scores_gemma":[0.00001394192,0.0001358031,0.00007201172,0.0001461284,0.0003482969,0.00004894266,0.00007134701,0.0004399352,0.000004768369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005724363,"about_ca_system_score_gemma":0.000007927198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.364296e-7,"about_ca_topic_score_gemma":9.041951e-9,"domain_scores_codex":[0.998951,0.00002417969,0.0003874638,0.0001355053,0.0002645332,0.0002372755],"domain_scores_gemma":[0.999494,0.00009833771,0.0001049936,0.0001990655,0.00003298216,0.00007058024],"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":[0.000653598,0.0002619534,3.440081e-7,0.00003341253,0.00002530842,8.338832e-7,0.0002903276,0.1138315,0.6158383,0.2690281,0.000002326855,0.00003397912],"study_design_scores_gemma":[0.001183944,0.002771857,0.000005267612,0.0001891876,0.00002995773,0.00002160816,0.00007415891,0.01582244,0.952013,0.02772316,0.00001561354,0.0001497819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994845,0.0002277751,0.003213962,0.0007294076,0.00005423519,0.0001610884,0.000004204137,0.00005601932,0.000708324],"genre_scores_gemma":[0.9996591,0.00004415031,0.0001396714,0.00003920676,0.00008536822,0.000005090928,0.000001006423,0.00002396116,0.000002472817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3361747,"threshold_uncertainty_score":0.5537888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006546675905711469,"score_gpt":0.244731072682256,"score_spread":0.2381843967765445,"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."}}