{"id":"W2245938272","doi":"10.14447/jnmes.v15i4.50","title":"Hydriding kinetics of LaNi&lt;sub&gt;5&lt;/sub&gt; using Nucleation-growth and Diffusion Models","year":2012,"lang":"en","type":"article","venue":"Journal of New Materials for Electrochemical Systems","topic":"Hydrogen Storage and Materials","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diffusion; Nucleation; Gravimetric analysis; Hydride; Thermodynamics; Kinetics; Alloy; Materials science; Phase (matter); Hydrogen; Chemistry; Physical chemistry; Metallurgy; Physics; Metal","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001230906,0.0003072931,0.0009902584,0.0001491109,0.0000962845,0.0001914771,0.0002964794,0.000255723,0.00003744267],"category_scores_gemma":[0.0002469262,0.0002513995,0.0001323291,0.0001235926,0.00005793774,0.0006292615,0.0001029036,0.00007857243,0.000005293361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001652782,"about_ca_system_score_gemma":0.00008521936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003521893,"about_ca_topic_score_gemma":9.460197e-7,"domain_scores_codex":[0.9969374,0.0001608556,0.0014201,0.0002372876,0.0006094604,0.0006348779],"domain_scores_gemma":[0.9976141,0.0001344773,0.001352129,0.0001976311,0.0003534759,0.0003481382],"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":[0.0003262921,0.0001026558,0.00001230392,0.0004122305,0.00003909969,0.000002708778,0.0002997243,0.00004130516,0.9973453,0.001029998,0.000369128,0.00001925042],"study_design_scores_gemma":[0.0008836665,0.0002731181,0.000007546408,0.0003242438,0.0001636972,0.0004062946,0.00002693332,0.000293003,0.9960762,0.0008596706,0.000421911,0.0002637399],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871935,0.001220639,0.00951892,0.0000367851,0.001516294,0.0004146443,0.00004182789,0.00002898383,0.00002835869],"genre_scores_gemma":[0.9964086,0.0001534368,0.001186558,0.00002835417,0.002129555,0.000008343158,0.000009380268,0.00006225994,0.00001344182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009215122,"threshold_uncertainty_score":0.9999938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02338759824798322,"score_gpt":0.2482862555272137,"score_spread":0.2248986572792304,"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."}}