{"id":"W2150883444","doi":"10.1155/2014/190320","title":"Thermodynamic Modeling of Hydrogen Storage Capacity in Mg-Na Alloys","year":2014,"lang":"en","type":"article","venue":"The Scientific World JOURNAL","topic":"Hydrogen Storage and Materials","field":"Materials Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"CALPHAD; Thermodynamics; Ternary operation; Phase diagram; Hydrogen storage; Work (physics); Ternary numeral system; Hydride; Materials science; Phase (matter); Hydrogen; Chemistry; Computer science; Physics; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001790237,0.0002490166,0.0003872725,0.0004410748,0.0003184149,0.0003883235,0.0007280573,0.0002719131,0.001282984],"category_scores_gemma":[0.0002466297,0.0001754328,0.0003530616,0.0004383927,0.0002364986,0.0005404127,0.0001923806,0.0001391849,0.0002505374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007285113,"about_ca_system_score_gemma":0.0005133538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004172293,"about_ca_topic_score_gemma":0.00349561,"domain_scores_codex":[0.9999307,0.000009328394,0.000006329225,0.00001151712,0.00003271773,0.000009414422],"domain_scores_gemma":[0.9999497,0.00001619635,0.000006219795,0.000009290926,0.00001527747,0.000003346785],"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":[0.0001267989,0.00006947696,0.004393136,0.0001490321,0.00003085198,0.0001839897,0.00005167533,0.8983987,0.0794814,0.008941023,0.0002514191,0.007922455],"study_design_scores_gemma":[0.00000584354,0.00002804806,0.001222133,0.000002793614,0.000005849786,0.00002571185,0.00001197593,0.9792855,0.01739994,0.001158056,0.0008467753,0.000007391607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9553301,0.000846011,0.03019247,0.0001025723,0.00001834247,0.00006264083,0.001277769,0.0002117229,0.01195841],"genre_scores_gemma":[0.9950179,0.0002306559,0.002766367,0.000006767236,0.000003760687,0.000043248,0.000406411,0.00002721255,0.001497676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004172293,"threshold_uncertainty_score":0.008296013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03337912993458792,"score_gpt":0.2399549919816596,"score_spread":0.2065758620470717,"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."}}