{"id":"W4393306539","doi":"10.1016/j.jmst.2024.03.009","title":"Hot extrusion-induced Mg-Ni-Y alloy with enhanced hydrogen storage kinetics","year":2024,"lang":"en","type":"article","venue":"Journal of Material Science and Technology","topic":"Hydrogen Storage and Materials","field":"Materials Science","cited_by":72,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; National University's Basic Research Foundation of China; National Natural Science Foundation of China","keywords":"Materials science; Hydrogen storage; Extrusion; Kinetics; Alloy; Metallurgy; Chemical engineering","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":[0.001437138,0.0002087944,0.0004036283,0.000617602,0.0002038627,0.0004355529,0.0006687838,0.000180242,0.0004482634],"category_scores_gemma":[0.0001437388,0.0001385521,0.00003071722,0.0008720415,0.0007546982,0.0006724765,0.000245503,0.0001581382,0.0000570063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001066153,"about_ca_system_score_gemma":0.0003984826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002093157,"about_ca_topic_score_gemma":0.000008695456,"domain_scores_codex":[0.9979221,0.00004472512,0.0005095421,0.0003876747,0.0006530678,0.0004828833],"domain_scores_gemma":[0.9989147,0.00002617652,0.0002563772,0.0002728775,0.0003608655,0.0001690004],"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":[0.00009444848,0.00003398803,0.00000482154,0.00003148816,0.000009327595,0.0003362019,0.0001454339,0.000003545344,0.9955171,0.0007776984,0.00009671807,0.00294919],"study_design_scores_gemma":[0.0002615559,0.0009557158,0.00002266772,0.0001346269,0.00003626062,0.001153457,0.0001190767,0.00001968722,0.9917338,0.0009987322,0.004375949,0.000188402],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962587,0.0002349374,0.0001517658,0.0006969854,0.002221289,0.0001469415,0.00001355207,0.0001273256,0.0001485486],"genre_scores_gemma":[0.9981627,0.00008255611,0.001286122,0.0000657246,0.0003139017,0.000007353063,5.625967e-7,0.00002080514,0.00006031288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004279231,"threshold_uncertainty_score":0.5649992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009203004527418467,"score_gpt":0.2471839551231281,"score_spread":0.2379809505957096,"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."}}