{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T16:57:50Z","timestamp":1780937870711,"version":"3.54.1"},"reference-count":59,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing Municipality","doi-asserted-by":"publisher","award":["CSTB2024NSCQ-MSX0512"],"award-info":[{"award-number":["CSTB2024NSCQ-MSX0512"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024YFC3016503"],"award-info":[{"award-number":["2024YFC3016503"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024YFC3016500"],"award-info":[{"award-number":["2024YFC3016500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52104181"],"award-info":[{"award-number":["52104181"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52174164"],"award-info":[{"award-number":["52174164"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Reliability Engineering &amp; System Safety"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ress.2026.112739","type":"journal-article","created":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T21:20:21Z","timestamp":1776028821000},"page":"112739","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"P1","title":["Dynamic evolution mechanism of mine accident risks: An interpretable machine learning framework for causal analysis"],"prefix":"10.1016","volume":"275","author":[{"given":"Haitao","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuyan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Limin","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenjing","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minggao","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ress.2026.112739_bib0001","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.ssci.2018.07.019","article-title":"Fatal accident patterns of building construction activities in China","volume":"111","author":"Shao","year":"2019","journal-title":"Saf Sci"},{"key":"10.1016\/j.ress.2026.112739_bib0002","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1016\/j.ssci.2019.04.038","article-title":"Identification of critical causes of construction accidents in China using a model based on system thinking and case analysis","volume":"121","author":"Zhang","year":"2020","journal-title":"Saf Sci"},{"key":"10.1016\/j.ress.2026.112739_bib0003","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.psep.2019.10.014","article-title":"Statistical analysis the characteristics of extraordinarily severe coal mine accidents (ESCMAs) in China from 1950 to 2018","volume":"133","author":"Zhang","year":"2020","journal-title":"Process Saf Environ Prot"},{"key":"10.1016\/j.ress.2026.112739_bib0004","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1186\/s12889-025-21583-0","article-title":"Exploring the economic occupational health, safety, and fatal accidents in high-risk industries","volume":"25","author":"Cao","year":"2025","journal-title":"BMC Public Health"},{"key":"10.1016\/j.ress.2026.112739_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.fuel.2023.127448","article-title":"Experimental preparation and mechanism analysis of a neotype composite gel for coal spontaneous combustion prevention and coal-fire extinguishment","volume":"339","author":"Yu","year":"2023","journal-title":"Fuel"},{"key":"10.1016\/j.ress.2026.112739_bib0006","article-title":"Reliability assessment of robustness for reinforced concrete moment resisting frames","volume":"21","author":"Miceli","year":"2025","journal-title":"Dev Built Environ"},{"key":"10.1016\/j.ress.2026.112739_bib0007","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.oneear.2021.03.005","article-title":"A framework for complex climate change risk assessment","volume":"4","author":"Simpson","year":"2021","journal-title":"One Earth"},{"key":"10.1016\/j.ress.2026.112739_bib0008","doi-asserted-by":"crossref","DOI":"10.1016\/j.worlddev.2020.105214","article-title":"Lessons for climate policy from behavioral biases towards COVID-19 and climate change risks","volume":"137","author":"Botzen","year":"2021","journal-title":"World Dev"},{"key":"10.1016\/j.ress.2026.112739_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2021.108047","article-title":"Guided simulation for dynamic probabilistic risk assessment of complex systems: concept, method, and application","volume":"217","author":"Hu","year":"2022","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2021.107791","article-title":"A novel risk evaluation method for fire and explosion accidents in oil depots using bow-tie analysis and risk matrix analysis method based on cloud model theory","volume":"215","author":"Xie","year":"2021","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.oceaneng.2021.109500","article-title":"Risk assessment of ship anchorage handling operations using the fuzzy bow-tie method","volume":"236","author":"Kaptan","year":"2021","journal-title":"Ocean Eng"},{"key":"10.1016\/j.ress.2026.112739_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.jclepro.2022.130780","article-title":"An adaptive safety-risk mitigation plan at process-level for sustainable production in chemical industries: an integrated fuzzy-HAZOP-best-worst approach","volume":"339","author":"Nguyen","year":"2022","journal-title":"J Clean Prod"},{"key":"10.1016\/j.ress.2026.112739_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109609","article-title":"A semi-quantitative risk assessment of remote handling operations on the SPES Front-end based on HAZOP-LOPA","volume":"241","author":"Lilli","year":"2024","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0014","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.ijhydene.2025.06.021","article-title":"Research on hydrogen leakage risk of HECS from the perspective of infrastructure safety resilience","volume":"144","author":"Wang","year":"2025","journal-title":"Int J Hydrog Energy"},{"key":"10.1016\/j.ress.2026.112739_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.ssci.2022.105989","article-title":"Identifying effective risk management frameworks for complex socio-technical systems","volume":"158","author":"Luther","year":"2023","journal-title":"Saf Sci"},{"key":"10.1016\/j.ress.2026.112739_bib0016","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.psep.2019.11.027","article-title":"The development history of accident causation models in the past 100 years: 24Model, a more modern accident causation model","volume":"134","author":"Fu","year":"2020","journal-title":"Process Saf Environ Prot"},{"key":"10.1016\/j.ress.2026.112739_bib0017","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.dss.2015.01.006","article-title":"A framework for model integration and holistic modelling of socio-technical systems","volume":"71","author":"Wu","year":"2015","journal-title":"Decis Support Syst"},{"key":"10.1016\/j.ress.2026.112739_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.112126","article-title":"Risk assessment for modern industry","volume":"269","author":"Pinciroli","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0019","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2026.112420","article-title":"Exploring cascade propagation mechanisms of flood risk in dynamic heterogeneous infrastructure networks: a systematic framework with a heterogeneity perspective","volume":"274","author":"Li","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2026.112564","article-title":"Dynamic risk analysis of bunkering operations based on system dynamics simulation and Bayesian network","author":"Khan","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2024.132533","article-title":"Risk evolution analysis of cross-regional water diversion projects based on spatio-temporal knowledge graphs","volume":"650","author":"Wang","year":"2025","journal-title":"J Hydrol"},{"key":"10.1016\/j.ress.2026.112739_bib0022","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.psep.2019.11.029","article-title":"Developing an advanced dynamic risk analysis method for fire-related domino effects","volume":"134","author":"Zeng","year":"2020","journal-title":"Process Saf Environ Prot"},{"key":"10.1016\/j.ress.2026.112739_bib0023","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2111997119","article-title":"Toward data-driven, dynamical complex systems approaches to disaster resilience","volume":"119","author":"Yabe","year":"2022","journal-title":"Proc Natl Acad Sci"},{"key":"10.1016\/j.ress.2026.112739_bib0024","doi-asserted-by":"crossref","DOI":"10.1016\/j.apenergy.2022.120620","article-title":"Dynamic bayesian network risk probability evolution for third-party damage of natural gas pipelines","volume":"333","author":"Hong","year":"2023","journal-title":"Appl Energy"},{"key":"10.1016\/j.ress.2026.112739_bib0025","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1177\/14761270221125807","article-title":"Overcoming path-dependent dynamic capabilities","volume":"23","author":"Keller","year":"2025","journal-title":"Strateg Organ"},{"key":"10.1016\/j.ress.2026.112739_bib0026","doi-asserted-by":"crossref","DOI":"10.1016\/j.gloenvcha.2021.102236","article-title":"Understanding interlinkages between long-term trajectory of exposure and vulnerability, path dependency and cascading impacts of disasters in Saint-Martin (Caribbean)","volume":"67","author":"Duvat","year":"2021","journal-title":"Glob Environ Change"},{"key":"10.1016\/j.ress.2026.112739_bib0027","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2020.107109","article-title":"A novel approach for domino effects modeling and risk analysis based on synergistic effect and accident evidence","volume":"203","author":"Ding","year":"2020","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.nucengdes.2023.112797","article-title":"Interplay of human factors and safety culture in nuclear safety for enhanced organisational and individual performance: a comprehensive review","volume":"416","author":"Felix Orikpete","year":"2024","journal-title":"Nucl Eng Des"},{"key":"10.1016\/j.ress.2026.112739_bib0029","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1080\/01441647.2022.2036864","article-title":"A survey of the opportunities and challenges of supervised machine learning in maritime risk analysis","volume":"43","author":"Rawson","year":"2023","journal-title":"Transp Rev"},{"key":"10.1016\/j.ress.2026.112739_bib0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2022.108859","article-title":"Supply chain risk management with machine learning technology: a literature review and future research directions","volume":"175","author":"Yang","year":"2023","journal-title":"Comput Ind Eng"},{"key":"10.1016\/j.ress.2026.112739_bib0031","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1007\/s10462-025-11175-0","article-title":"Application of machine learning in early warning system of geotechnical disaster: a systematic and comprehensive review","volume":"58","author":"Lin","year":"2025","journal-title":"Artif Intell Rev"},{"key":"10.1016\/j.ress.2026.112739_bib0032","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1007\/s10462-024-10898-w","article-title":"Application of artificial intelligence in coal mine ultra-deep roadway engineering\u2014A review","volume":"57","author":"Yu","year":"2024","journal-title":"Artif Intell Rev"},{"key":"10.1016\/j.ress.2026.112739_bib0033","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2021.107530","article-title":"Machine learning for reliability engineering and safety applications: review of current status and future opportunities","volume":"211","author":"Xu","year":"2021","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0034","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111839","article-title":"Dynamic ensemble-learning model for seismic risk assessment of masonry infilled steel structures incorporating soil-foundation-structure interaction","volume":"267","author":"Asgarkhani","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2026.112190","article-title":"A deep reinforcement learning approach for robust dynamic Bayesian network-based systemic risk analysis in freight forwarding","volume":"271","author":"Wang","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.112156","article-title":"DB-DDPG-ET: a novel risk assessment framework for crowd safety during boarding & alighting process at subway platforms","volume":"270","author":"Xu","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0037","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","article-title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead","volume":"1","author":"Rudin","year":"2019","journal-title":"Nat Mach Intell"},{"key":"10.1016\/j.ress.2026.112739_bib0038","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s12559-023-10179-8","article-title":"Interpreting black-box models: a review on explainable artificial intelligence","volume":"16","author":"Hassija","year":"2024","journal-title":"Cogn Comput"},{"key":"10.1016\/j.ress.2026.112739_bib0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.aap.2022.106617","article-title":"On the interpretability of machine learning methods in crash frequency modeling and crash modification factor development","volume":"168","author":"Wen","year":"2022","journal-title":"Accid Anal Prev"},{"key":"10.1016\/j.ress.2026.112739_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111294","article-title":"Exploring the perspective of time: a framework for dynamic assessment of leakage risk in WDNs based on a joint model of survival analysis and machine learning","volume":"264","author":"Kang","year":"2025","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0041","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.112028","article-title":"Improved AHP and dual-hidden layer adaptive regularized neural network model for the quantitative risk assessment of oil and gas pipelines","volume":"268","author":"Qu","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0042","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2026.112212","article-title":"Probabilistic risk uncertainty assessment for driver over-trust and under-trust in level 3 human-automated driving systems cooperative driving based on the drift-diffusion model","volume":"271","author":"Ding","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0043","doi-asserted-by":"crossref","first-page":"0467","DOI":"10.34133\/research.0467","article-title":"Causal inference meets deep learning: a comprehensive survey","volume":"7","author":"Jiao","year":"2024","journal-title":"Research"},{"key":"10.1016\/j.ress.2026.112739_bib0044","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1162\/tacl_a_00335","article-title":"An empirical study on robustness to spurious correlations using pre-trained language models","volume":"8","author":"Tu","year":"2020","journal-title":"Trans Assoc Comput Linguist"},{"key":"10.1016\/j.ress.2026.112739_bib0045","doi-asserted-by":"crossref","first-page":"2097","DOI":"10.1111\/risa.17708","article-title":"Applications of interpretable ensemble learning for workplace risk assessment: the Chinese coal industry as an example","volume":"45","author":"Wang","year":"2025","journal-title":"Risk Anal"},{"key":"10.1016\/j.ress.2026.112739_bib0046","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/s40948-024-00761-1","article-title":"Research on the prediction of mine water inrush disasters based on multi-factor spatial game reconstruction","volume":"10","author":"Zheng","year":"2024","journal-title":"Geomech Geophys Geo-Energy Geo-Resour"},{"key":"10.1016\/j.ress.2026.112739_bib0047","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2023.119748","article-title":"Interpretable belief rule base for safety state assessment with reverse causal inference","volume":"651","author":"Yin","year":"2023","journal-title":"Inf Sci"},{"key":"10.1016\/j.ress.2026.112739_bib0048","unstructured":"Mine Safety and Health Administration (MSHA). Mine data retrieval system (MDRS) 2025. https:\/\/www.msha.gov\/mine-data-retrieval-system."},{"key":"10.1016\/j.ress.2026.112739_bib0049","unstructured":"Federal mine safety and health Act of 1977. vol. 30. 1977."},{"key":"10.1016\/j.ress.2026.112739_bib0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.112026","article-title":"Machine learning modelling of structural response for different seismic signal characteristics: a parametric analysis","volume":"164","author":"De Iuliis","year":"2024","journal-title":"Appl Soft Comput"},{"key":"10.1016\/j.ress.2026.112739_bib0051","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2025.120448","article-title":"Information theory-guided machine learning to estimate seismic response of non-linear SDOF structures","volume":"336","author":"De Iuliis","year":"2025","journal-title":"Eng Struct"},{"key":"10.1016\/j.ress.2026.112739_bib0052","article-title":"A unified approach to interpreting model predictions","volume":"30","author":"Lundberg","year":"2017"},{"key":"10.1016\/j.ress.2026.112739_bib0053","doi-asserted-by":"crossref","first-page":"C1","DOI":"10.1111\/ectj.12097","article-title":"Double\/debiased machine learning for treatment and structural parameters","volume":"21","author":"Chernozhukov","year":"2018","journal-title":"Econom J"},{"key":"10.1016\/j.ress.2026.112739_bib0054","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1177\/0170840610397481","article-title":"Organizational path dependence: a process view","volume":"32","author":"Schrey\u00f6gg","year":"2011","journal-title":"Organ Stud"},{"key":"10.1016\/j.ress.2026.112739_bib0055","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.jbusres.2022.02.040","article-title":"How to overcome path dependency through resource reconfiguration","volume":"145","author":"Goumagias","year":"2022","journal-title":"J Bus Res"},{"key":"10.1016\/j.ress.2026.112739_bib0056","series-title":"Critical phenomena in natural sciences: chaos, fractals, selforganization, and disorder: concepts and tools","author":"Sornette","year":"2004"},{"key":"10.1016\/j.ress.2026.112739_bib0057","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1038\/nature08227","article-title":"Early-warning signals for critical transitions","volume":"461","author":"Scheffer","year":"2009","journal-title":"Nature"},{"key":"10.1016\/j.ress.2026.112739_bib0058","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111688","article-title":"Control strategies for order\u2013disorder phase transition in crowd evacuation","volume":"266","author":"Yi","year":"2026","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2026.112739_bib0059","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2025.111254","article-title":"Mixed shock model for the multi-state system with a two-phase degradation process under Markov environment","volume":"264","author":"Lyu","year":"2025","journal-title":"Reliab Eng Syst Saf"}],"container-title":["Reliability Engineering &amp; System Safety"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026005508?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0951832026005508?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T15:58:34Z","timestamp":1780934314000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0951832026005508"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":59,"alternative-id":["S0951832026005508"],"URL":"https:\/\/doi.org\/10.1016\/j.ress.2026.112739","relation":{},"ISSN":["0951-8320"],"issn-type":[{"value":"0951-8320","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Dynamic evolution mechanism of mine accident risks: An interpretable machine learning framework for causal analysis","name":"articletitle","label":"Article Title"},{"value":"Reliability Engineering & System Safety","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ress.2026.112739","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"112739"}}