{"id":"W3150063888","doi":"10.1016/j.pmatsci.2021.100798","title":"Pathway to understand liquid metal embrittlement (LME) in Fe-Zn couple: From fundamentals toward application","year":2021,"lang":"en","type":"article","venue":"Progress in Materials Science","topic":"Hydrogen embrittlement and corrosion behaviors in metals","field":"Materials Science","cited_by":115,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Liquid metal embrittlement; Materials science; Embrittlement; Grain boundary; Metallurgy; Brazing; Welding; Mechanism (biology); Alloy; Microstructure","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003266592,0.0003261385,0.000560365,0.0002946846,0.0002264583,0.0006727051,0.001085466,0.00009908256,0.002607765],"category_scores_gemma":[0.0001141249,0.0003203271,0.00005394882,0.001308725,0.000557406,0.0006468954,0.0008279048,0.0001082196,0.0003613544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000455574,"about_ca_system_score_gemma":0.0004203797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001676165,"about_ca_topic_score_gemma":0.0001959063,"domain_scores_codex":[0.9951855,0.0002621856,0.001014107,0.001311428,0.001317666,0.0009090994],"domain_scores_gemma":[0.9985709,0.00006063208,0.000238421,0.0007212756,0.0001663966,0.0002423865],"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":[0.00009972121,0.0003077616,0.003878616,0.00002779435,0.000001784893,0.00005615236,0.000918166,0.00003563287,0.9922701,0.0009236276,0.00001445423,0.001466253],"study_design_scores_gemma":[0.0005883689,0.0001253979,0.003389235,0.0001312967,0.00001329104,0.000006465944,0.001140835,0.00006472581,0.9930608,0.0006583028,0.000427246,0.0003939971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953709,0.0006130218,0.0008825238,0.0004526816,0.001351092,0.0009382861,0.0001910065,0.00008026527,0.0001202335],"genre_scores_gemma":[0.9933027,0.00004591058,0.005693594,0.0002783987,0.00009151016,0.0004381455,0.00006353206,0.00002774716,0.00005844679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00481107,"threshold_uncertainty_score":0.9999249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03090596217990959,"score_gpt":0.3103725886713641,"score_spread":0.2794666264914545,"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."}}