{"id":"W4415445722","doi":"10.1016/j.ress.2025.111790","title":"Exploring incident patterns in the hydrogen value chain using knowledge graphs: A roadmap toward targeted risk control","year":2025,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Graph theory; Graph; Causation; Hazard; Hazard analysis; Energy carrier; Value (mathematics)","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":[0.001657244,0.0009614048,0.0006683109,0.006309872,0.0006390553,0.003077714,0.001682632,0.001087381,0.002764476],"category_scores_gemma":[0.01252472,0.0004910818,0.001234196,0.005220673,0.0008867402,0.006111898,0.001678776,0.00146037,0.0003761822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001308821,"about_ca_system_score_gemma":0.002776447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02484387,"about_ca_topic_score_gemma":0.03257651,"domain_scores_codex":[0.9986236,0.0005275941,0.0001186361,0.0003035815,0.0003204494,0.0001060562],"domain_scores_gemma":[0.9882858,0.00804914,0.001187439,0.001195144,0.0009362492,0.0003462725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003951267,0.001026774,0.1038613,0.001290201,0.000817333,0.001062908,0.002088443,0.40329,0.004731342,0.093908,0.009991706,0.3775369],"study_design_scores_gemma":[0.00003295768,0.00009940632,0.01047789,0.0003604493,0.0001994965,0.0001650739,0.001931884,0.6608137,0.002175788,0.3097346,0.01394297,0.00006571053],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.217839,0.00200387,0.7465515,0.00657976,0.00009956385,0.0008198922,0.01232879,0.002228318,0.0115494],"genre_scores_gemma":[0.6802142,0.001712232,0.3074324,0.0004593523,0.00003303727,0.0002385121,0.008327857,0.0001255844,0.001456788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02484387,"threshold_uncertainty_score":0.04939854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05984507028434012,"score_gpt":0.3018842109098462,"score_spread":0.2420391406255061,"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."}}