{"id":"W2068705926","doi":"10.1007/s11661-012-1412-1","title":"An Interface-Enriched eXtended Finite Element-Level Set Simulation of Solutal Melting of Additive Powder Particles during Transient Liquid Phase Bonding","year":2012,"lang":"en","type":"article","venue":"Metallurgical and Materials Transactions A","topic":"Aluminum Alloys Composites Properties","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Diffusion; Transient (computer programming); Phase (matter); Finite element method; Alloy; Matching (statistics); Substrate (aquarium); Discrete element method; Mechanics; Thermodynamics; Composite material; Computer science; Chemistry; Physics","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":[0.0002173178,0.0001655128,0.0003241674,0.00008449861,0.00007958507,0.00002888101,0.00006218114,0.00006481708,0.0005795703],"category_scores_gemma":[0.00001020946,0.0001565279,0.00006583003,0.00009364915,0.00007210355,0.0004092419,0.00000681302,0.00006406186,0.000002129082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002045468,"about_ca_system_score_gemma":0.000006116933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001803966,"about_ca_topic_score_gemma":0.00000583798,"domain_scores_codex":[0.9988651,0.00007811483,0.0005014178,0.0001427237,0.0001398482,0.0002727736],"domain_scores_gemma":[0.9995922,0.00005725852,0.00007330588,0.0001109561,0.00004245927,0.0001238404],"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":[0.0003181961,0.0002225808,0.000001055327,0.0001330002,0.0001359982,0.000001009183,0.002258975,0.1131682,0.8831793,0.00002336741,3.352994e-7,0.000557985],"study_design_scores_gemma":[0.001177307,0.0003083199,0.0003811674,0.00005467522,0.000157797,0.0000121837,0.0005377419,0.08986411,0.9071956,0.000008187858,0.0001023944,0.0002005318],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7851063,0.0001538881,0.2142271,0.000006750744,0.0001136743,0.0001607173,0.0001525505,0.00006502213,0.00001398323],"genre_scores_gemma":[0.9985641,0.00003573018,0.001252276,0.000002954009,0.00003847912,0.00003274442,0.00002507502,0.0000289152,0.00001967255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2134578,"threshold_uncertainty_score":0.6383023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03323259128603533,"score_gpt":0.2784006784397143,"score_spread":0.2451680871536789,"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."}}