{"id":"W2006350523","doi":"10.1007/s11661-007-9388-y","title":"Quantitative Thermal Analysis of Transient Liquid-Phase-Sintered Cu-Ni Powders","year":2007,"lang":"en","type":"article","venue":"Metallurgical and Materials Transactions A","topic":"Advanced materials and composites","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Isothermal process; Materials science; Solidus; Liquidus; Differential scanning calorimetry; Sintering; Phase (matter); Dissolution; Analytical Chemistry (journal); Liquid phase; Eutectic system; Melting point; Atmospheric temperature range; Metallurgy; Chemical engineering; Microstructure; Thermodynamics; Composite material; Chromatography; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001966966,0.00015533,0.0004751412,0.0001729753,0.00005635685,0.0000363703,0.00006396977,0.00006858449,0.001317868],"category_scores_gemma":[0.000001868734,0.0001378732,0.0001292445,0.0002881312,0.00006765188,0.0001189603,0.000003340672,0.00004663249,0.000003694001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000011157,"about_ca_system_score_gemma":0.000003543734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006762328,"about_ca_topic_score_gemma":0.00007851124,"domain_scores_codex":[0.9990602,0.00002927544,0.0004307618,0.0001651943,0.0001030089,0.0002116052],"domain_scores_gemma":[0.9996892,0.00004894756,0.00004243893,0.0001050066,0.00003175123,0.00008261702],"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":[0.0004749369,0.0001180363,1.749882e-7,0.00005383789,0.0008520865,0.00001026418,0.0002924473,0.01387989,0.9831099,0.0004202839,0.000001008081,0.0007871338],"study_design_scores_gemma":[0.001268555,0.0005675792,0.0008194958,0.00003438849,0.001831418,0.00001250881,0.0003417889,0.005683844,0.9878191,0.0000587115,0.001181886,0.0003807395],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5778061,0.0001226536,0.4215753,0.00001034751,0.0001606403,0.00007055078,0.00007009524,0.00006137175,0.0001229976],"genre_scores_gemma":[0.9967378,0.0001481243,0.00300266,0.00001115262,0.000014845,0.00001192637,0.00002309688,0.00001791766,0.00003241653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4189318,"threshold_uncertainty_score":0.999595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01502040623984006,"score_gpt":0.2697058300630299,"score_spread":0.2546854238231899,"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."}}