{"id":"W4313472678","doi":"10.3390/ma16010383","title":"A Phase-Field Model for In-Space Manufacturing of Binary Alloys","year":2022,"lang":"en","type":"article","venue":"Materials","topic":"Solidification and crystal growth phenomena","field":"Materials Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; Nova Scotia Department of Energy; Nuclear Safety and Security Commission; University of Alabama; Advanced Research Projects Agency - Energy; National Aeronautics and Space Administration; Office of Experimental Program to Stimulate Competitive Research; Advanced Research Projects Agency; National Science Foundation","keywords":"Materials science; Microstructure; Supercooling; Phase (matter); Binary number; Ternary operation; Alloy; Field (mathematics); Mechanics; Phase space; Thermodynamics; Composite material; Physics; Mathematics; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000312617,0.0006287597,0.0007075307,0.000600749,0.0005590146,0.0006974187,0.001220553,0.002069498,0.002854571],"category_scores_gemma":[0.0006300816,0.0003572725,0.0006976909,0.000540302,0.0008373496,0.001159547,0.0004913965,0.0009348899,0.00050779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125953,"about_ca_system_score_gemma":0.0009474774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007489923,"about_ca_topic_score_gemma":0.003190532,"domain_scores_codex":[0.9998813,0.00003015887,0.000004965512,0.00002616503,0.00003727691,0.0000200504],"domain_scores_gemma":[0.9998697,0.00004964297,0.00002306507,0.000009824992,0.00003562062,0.00001204047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003820774,0.00006699033,0.0003275522,0.00008355491,0.000009881808,0.0001455801,0.00007969324,0.8727594,0.01824404,0.1047934,0.000690968,0.002760749],"study_design_scores_gemma":[0.000007989194,0.00001019455,0.00005409955,0.000002603608,0.000002106996,0.00001455893,0.00000459389,0.9953289,0.0005606557,0.003546795,0.000463333,0.000004182214],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1440453,0.001731713,0.8156283,0.001401731,0.0002646519,0.0002295092,0.0006489853,0.0002578562,0.03579191],"genre_scores_gemma":[0.8933659,0.001387843,0.06705303,0.0003324632,0.00009330687,0.0004884843,0.0003127386,0.00009875444,0.03686752],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007489923,"threshold_uncertainty_score":0.01489264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03779754082378391,"score_gpt":0.2923727319831514,"score_spread":0.2545751911593675,"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."}}