{"id":"W2609498671","doi":"10.1007/s41230-017-6092-4","title":"Characterization and kinetic modeling of secondary phases in squeeze cast Al alloy A380 by DSC thermal analysis","year":2017,"lang":"en","type":"article","venue":"China Foundry","topic":"Aluminum Alloy Microstructure Properties","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Microstructure; Materials science; Differential scanning calorimetry; Eutectic system; Alloy; Cooling curve; Dissolution; Kinetic energy; Scanning electron microscope; Activation energy; Thermodynamics; Precipitation; Phase (matter); Thermal analysis; Analytical Chemistry (journal); Thermal; Metallurgy; Composite material; Chemistry; Physical chemistry; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007404036,0.0001637264,0.0002753156,0.0001288312,0.0000940201,0.00009580042,0.0001865314,0.00007036627,0.00007503905],"category_scores_gemma":[0.00001871642,0.0001562367,0.0000531268,0.00007709963,0.0000863026,0.0003651861,0.00006203473,0.0001520943,0.000001635326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003368303,"about_ca_system_score_gemma":0.00001343059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003031686,"about_ca_topic_score_gemma":0.0001385408,"domain_scores_codex":[0.9992863,0.00001529007,0.0002466172,0.0001818676,0.00009218913,0.0001777296],"domain_scores_gemma":[0.9995537,0.000008426987,0.00006996837,0.0003071717,0.00002243155,0.00003830314],"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":[0.00002351069,0.00001627917,0.009039183,0.00007717836,0.000175008,0.000005702145,0.001122937,0.02335759,0.9606931,0.000007479142,0.0000184842,0.005463603],"study_design_scores_gemma":[0.000817347,0.0000398251,0.1333521,0.00005886673,0.0001854947,0.00001166516,0.00005919349,0.8321702,0.03252175,0.0000352127,0.0003637363,0.0003846017],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961174,0.0006387651,0.002475604,0.00003735469,0.0001305622,0.0001004095,0.00004791551,0.00004345907,0.0004085007],"genre_scores_gemma":[0.9994515,0.0001023284,0.0001873316,0.00002108034,0.0000403084,0.000006667857,0.00008162976,0.00002999626,0.00007911633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9281713,"threshold_uncertainty_score":0.6371149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007996210783424707,"score_gpt":0.2114428222124012,"score_spread":0.2034466114289765,"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."}}