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Intrusion Detection Using Random Forests Classifier with SMOTE and Feature Reduction
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-0-387-21606-5openalex-snapshot
The Elements of Statistical Learning
inferredcites →https://doi.org/10.1007/s11047-006-9026-4openalex-snapshot
Immune system approaches to intrusion detection – a review
inferredcites →https://doi.org/10.1016/j.eswa.2012.07.009openalex-snapshot
A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier
inferredcites →https://doi.org/10.1016/j.protcy.2012.05.017openalex-snapshot
Intrusion Detection using Naive Bayes Classifier with Feature Reduction
inferredcites →https://doi.org/10.1109/chinacom.2006.344739openalex-snapshot
Intrusion Detection System Based on Feature Selection and Support Vector Machine
inferredcites →https://doi.org/10.1109/cisda.2009.5356528openalex-snapshot
A detailed analysis of the KDD CUP 99 data set
inferredcites →https://doi.org/10.1109/iccisci.2012.6297095openalex-snapshot
An approach towards intrusion detection using PCA feature subsets and SVM
inferredcites →https://doi.org/10.1109/isda.2010.5687239openalex-snapshot
Principle components analysis and Support Vector Machine based Intrusion Detection System
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.26634/jse.1.4.731openalex-snapshot
Fuzzy Data Mining and Genetic Algorithms Applied to Intrusion Detection
inferredcites →https://doi.org/10.3923/itj.2011.648.655openalex-snapshot
A K-Means and Naive Bayes Learning Approach for Better Intrusion Detection
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inferred← citeshttps://doi.org/10.1002/9781119682806.ch3openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9781119795667.ch13openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/9781394230600.ch4openalex-snapshot
Class‐Imbalanced Problems in Malware Analysis and Detection in Classification Algorithms
inferred← citeshttps://doi.org/10.1002/ett.4062openalex-snapshot
Intelligent intrusion detection system in smart grid using computational intelligence and machine learning
inferred← citeshttps://doi.org/10.1002/spy2.70166openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-19807-7_2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-39442-4_53openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-76794-5_7openalex-snapshot
AI for Cybersecurity: ML-Based Techniques for Intrusion Detection Systems
inferred← citeshttps://doi.org/10.1007/978-3-031-90723-4_6openalex-snapshot
Real-Time Network Intrusion Detection System Using Machine Learning
inferred← citeshttps://doi.org/10.1007/978-3-032-18282-1_10openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-25187-9_2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-319-98776-7_133openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-319-99807-7_20openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-81-322-2695-6_45openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-13-1132-1_21openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-33-4673-4_45openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-33-4996-4_11openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-95-0140-3_38openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-99-9788-6_14openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s00521-023-08398-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s00779-019-01332-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10207-023-00792-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10489-022-03995-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10586-025-05194-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10922-026-10067-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11063-015-9457-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11227-025-08044-6openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s12652-021-03411-6openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s13369-017-2844-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s13369-025-10358-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s40747-022-00739-0openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s44163-024-00120-9openalex-snapshot
Self-healing hybrid intrusion detection system: an ensemble machine learning approach
inferred← citeshttps://doi.org/10.1007/s44196-022-00171-9openalex-snapshot
SMMO-CoFS: Synthetic Multi-minority Oversampling with Collaborative Feature Selection for Network Intrusion Detection System
inferred← citeshttps://doi.org/10.1016/j.adhoc.2020.102177openalex-snapshot
IGAN-IDS: An imbalanced generative adversarial network towards intrusion detection system in ad-hoc networks
inferred← citeshttps://doi.org/10.1016/j.array.2025.100406openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.comnet.2020.107315openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cose.2021.102289openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cose.2022.102810openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.eswa.2025.126718openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ins.2024.121407openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.patrec.2018.01.003openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.procs.2017.12.204openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.procs.2019.11.170openalex-snapshot
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inferred← citeshttps://doi.org/10.1049/ise2/1954901openalex-snapshot
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inferred← citeshttps://doi.org/10.1063/5.0266603openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/15578771.2025.2485061openalex-snapshot
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inferred← citeshttps://doi.org/10.1088/1742-6596/1192/1/012018openalex-snapshot
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inferred← citeshttps://doi.org/10.1088/1757-899x/569/5/052008openalex-snapshot
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inferred← citeshttps://doi.org/10.1088/1757-899x/612/5/052051openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2019.2933165openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2019.2935142openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2020.2973219openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2023.3247512openalex-snapshot
An Asynchronous Federated Learning Arbitration Model for Low-Rate DDoS Attack Detection
inferred← citeshttps://doi.org/10.1109/access.2023.3341755openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2024.3431534openalex-snapshot
A Novel IDS Based on Jaya Optimizer and Smote-ENN for Cyberattacks Detection
inferred← citeshttps://doi.org/10.1109/acct.2015.131openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/aiipcc57291.2022.00016openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/asiancon55314.2022.9909471openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ciscsd63381.2024.00040openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/cscloud.2017.15openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/cts.2016.0078openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/dasc/picom/cbdcom/cyberscitech.2019.00054openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/gcat62922.2024.10923970openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ic2pct60090.2024.10486584openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ic2pct68894.2026.11584349openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icaisc64594.2025.10959678openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icatcct.2017.8389109openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icbats54253.2022.9759062openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iccca52192.2021.9666265openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iccubea.2018.8697692openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icecct56650.2023.10179781openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iceeict53079.2022.9768557openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icesc48915.2020.9155656openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iciscn64258.2025.10934650openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icit52682.2021.9491694openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iconeei55709.2022.9972265openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icosst.2015.7396401openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icpsasia48933.2020.9208609openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icrito56286.2022.9964997openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icsidempc49020.2020.9299598openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/iip57348.2022.00070openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/indicon63790.2024.10958487openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/jas.2021.1004344openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/jiot.2021.3084796openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/jiot.2023.3342638openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/jiot.2025.3533918openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/missf68264.2026.11521974openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/segre58867.2023.00019openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ssci47803.2020.9308206openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tetci.2021.3074916openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tetci.2022.3170515openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tia.2021.3128469openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tnse.2025.3644385openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tnsm.2024.3406934openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/vtc2023-fall60731.2023.10333498openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/worlds450073.2020.9210329openalex-snapshot
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inferred← citeshttps://doi.org/10.1142/s0219467824500463openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3178582openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3689933.3690833openalex-snapshot
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inferred← citeshttps://doi.org/10.11591/ijai.v13.i1.pp711-721openalex-snapshot
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inferred← citeshttps://doi.org/10.1186/s13638-016-0623-3openalex-snapshot
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inferred← citeshttps://doi.org/10.14257/ijsia.2016.10.8.13openalex-snapshot
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inferred← citeshttps://doi.org/10.14569/ijacsa.2015.060922openalex-snapshot
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inferred← citeshttps://doi.org/10.14569/ijacsa.2016.070109openalex-snapshot
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inferred← citeshttps://doi.org/10.17929/tqs.5.64openalex-snapshot
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inferred← citeshttps://doi.org/10.22214/ijraset.2022.44253openalex-snapshot
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inferred← citeshttps://doi.org/10.28925/2663-4023.2026.32.1204openalex-snapshot
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inferred← citeshttps://doi.org/10.31987/ijict.1.3.40openalex-snapshot
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inferred← citeshttps://doi.org/10.3233/ida-173624openalex-snapshot
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inferred← citeshttps://doi.org/10.32628/ijsrst251257openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/s22031154openalex-snapshot
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inferred← citeshttps://doi.org/10.34768/amcs-2020-0025openalex-snapshot
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inferred← citeshttps://doi.org/10.3934/mbe.2023615openalex-snapshot
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inferred← citeshttps://doi.org/10.46481/asr.2025.4.3.327openalex-snapshot
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inferred← citeshttps://doi.org/10.48550/arxiv.1807.06538openalex-snapshot
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inferred← citeshttps://doi.org/10.5120/16286-6185openalex-snapshot
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inferred← citeshttps://doi.org/10.5120/ijca2015906771openalex-snapshot
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inferred← citeshttps://doi.org/10.5815/ijcnis.2015.03.05openalex-snapshot
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inferred← citeshttps://doi.org/10.6339/24-jds1154openalex-snapshot
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inferred← citeshttps://doi.org/10.70675/e2fe5f32z19e5z41caz9b55z7b33b874c3c0openalex-snapshot
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inferred← citeshttps://doi.org/10.7176/ceis/10-7-02openalex-snapshot
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inferred← citeshttps://doi.org/10.9790/1813-0601029397openalex-snapshot
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