{"id":"W2606930095","doi":"10.1016/j.ijhydene.2017.03.213","title":"Corrigendum to “In-situ neutron diffraction investigation of Mg2FeH6 dehydrogenation” [Int J Hydrogen Energy 42 (2017) 3087–3096]","year":2017,"lang":"en","type":"erratum","venue":"International Journal of Hydrogen Energy","topic":"Hydrogen Storage and Materials","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières; Canadian Nuclear Laboratories","funders":"","keywords":"Dehydrogenation; Neutron diffraction; In situ; Materials science; Hydrogen; Hydrogen storage; INT; Diffraction; Chemistry; Crystallography; Physics; Crystal structure; Computer science; Optics; Catalysis; Organic 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001536915,0.0008223265,0.001545707,0.001797394,0.0001989451,0.0003435074,0.003062361,0.0008895634,0.0005703325],"category_scores_gemma":[0.0004054348,0.0008008943,0.000650875,0.0002637191,0.0002353692,0.00121677,0.000532677,0.0005941578,0.0001096237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069085,"about_ca_system_score_gemma":0.001150575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002661659,"about_ca_topic_score_gemma":0.002210861,"domain_scores_codex":[0.992507,0.0004904961,0.002816008,0.0008704123,0.002566311,0.0007497403],"domain_scores_gemma":[0.9916046,0.00009518638,0.005118594,0.0009591975,0.001664163,0.0005582799],"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":[0.0003854953,0.0002187767,0.00007331463,0.00005075672,0.0004030371,0.0007819223,0.0003324041,0.001249623,0.8743589,0.001131583,0.1193872,0.001627023],"study_design_scores_gemma":[0.0008427464,0.0002639639,0.0001925787,0.0006086107,0.0001479295,0.0006499065,0.00003224047,0.0001507161,0.6186785,0.001727084,0.3761275,0.0005782745],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.903663,0.00342378,0.0007865675,0.001073306,0.08440366,0.0002941202,0.0003699908,0.00007307139,0.0059125],"genre_scores_gemma":[0.9661028,0.00250425,0.000357724,0.0007159715,0.00654472,0.00006579073,0.0005767488,0.0001713179,0.02296064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2567403,"threshold_uncertainty_score":0.9994442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02438562010430843,"score_gpt":0.272401526498553,"score_spread":0.2480159063942446,"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."}}