{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:57:55Z","timestamp":1772823475827,"version":"3.50.1"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,2,28]],"date-time":"2020-02-28T00:00:00Z","timestamp":1582848000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,2,28]],"date-time":"2020-02-28T00:00:00Z","timestamp":1582848000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2020,5]]},"DOI":"10.1007\/s10994-020-05869-5","type":"journal-article","created":{"date-parts":[[2020,2,28]],"date-time":"2020-02-28T19:02:41Z","timestamp":1582916561000},"page":"1039-1099","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Joint maximization of accuracy and information for learning the structure of a Bayesian network classifier"],"prefix":"10.1007","volume":"109","author":[{"given":"Dan","family":"Halbersberg","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maydan","family":"Wienreb","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boaz","family":"Lerner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,2,28]]},"reference":[{"key":"5869_CR1","volume-title":"An introduction to categorical data analysis","author":"A Agresti","year":"2011","unstructured":"Agresti, A. (2011). An introduction to categorical data analysis. Berlin: Springer."},{"key":"5869_CR2","doi-asserted-by":"crossref","unstructured":"Baccianella, S., Esuli, A., & Sebastiani, F. (2009). Evaluation measures for ordinal regression. In Proceedings of the ninth international conference on intelligent systems design and applications (pp. 283\u2013287). IEEE.","DOI":"10.1109\/ISDA.2009.230"},{"issue":"5","key":"5869_CR3","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1093\/bioinformatics\/16.5.412","volume":"16","author":"P Baldi","year":"2000","unstructured":"Baldi, P., Brunak, S., Chauvin, Y., Andersen, C. A., & Nielsen, H. (2000). Assessing the accuracy of prediction algorithms for classification: An overview. Bioinformatics, 16(5), 412\u2013424.","journal-title":"Bioinformatics"},{"key":"5869_CR4","volume-title":"Classification and regression trees","author":"L Breiman","year":"1984","unstructured":"Breiman, L., Friedman, J., Stone, C. J., & Olshen, R. A. (1984). Classification and regression trees. Boca Raton: CRC Press."},{"key":"5869_CR5","doi-asserted-by":"crossref","unstructured":"Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010). The balanced accuracy and its posterior distribution. In Proceedings of the 20th international conference on pattern recognition (pp. 3121\u20133124). IEEE.","DOI":"10.1109\/ICPR.2010.764"},{"issue":"2","key":"5869_CR6","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1001\/archneur.1996.00550020045014","volume":"53","author":"BR Brooks","year":"1996","unstructured":"Brooks, B. R., Sanjack, M., Ringel, S., England, J., Brinkmann, J., Pestronk, A., et al. (1996). The amyotrophic lateral sclerosis functional rating scale-assessment of activities of daily living in patients with amyotrophic lateral sclerosis. Archives of Neurology, 53(2), 141\u2013147.","journal-title":"Archives of Neurology"},{"issue":"5","key":"5869_CR7","doi-asserted-by":"publisher","first-page":"750","DOI":"10.1109\/TNN.2010.2041468","volume":"21","author":"JCF Caballero","year":"2010","unstructured":"Caballero, J. C. F., Mart\u00ednez, F. J., Herv\u00e1s, C., & Guti\u00e9rrez, P. A. (2010). Sensitivity versus accuracy in multiclass problems using memetic pareto evolutionary neural networks. IEEE Transactions on Neural Networks, 21(5), 750\u2013770.","journal-title":"IEEE Transactions on Neural Networks"},{"key":"5869_CR8","doi-asserted-by":"crossref","unstructured":"Chang, C. C., & Lin, C. J. (2011). LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology,2(3):27, http:\/\/www.csie.ntu.edu.tw\/~cjlin\/libsvm","DOI":"10.1145\/1961189.1961199"},{"key":"5869_CR9","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"N Chawla","year":"2002","unstructured":"Chawla, N., Bowyer, K., Hall, L., & Kegelmeyer, W. (2002). SMOTE: Synthetic minority over-sampling technique. Journal of Artificial Intelligence Research, 16, 321\u2013357.","journal-title":"Journal of Artificial Intelligence Research"},{"key":"5869_CR10","doi-asserted-by":"crossref","unstructured":"Chawla, N. V. (2005). Data mining for imbalanced datasets: An overview. In Data mining and knowledge discovery handbook (pp. 853\u2013867).","DOI":"10.1007\/0-387-25465-X_40"},{"issue":"4","key":"5869_CR11","first-page":"309","volume":"9","author":"GF Cooper","year":"1992","unstructured":"Cooper, G. F., & Herskovits, E. (1992). A Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9(4), 309\u2013347.","journal-title":"Machine Learning"},{"key":"5869_CR12","volume-title":"Elements of information theory","author":"TM Cover","year":"2012","unstructured":"Cover, T. M., & Thomas, J. A. (2012). Elements of information theory. New York: Wiley."},{"key":"5869_CR13","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar, J. (2006). Statistical comparisons of classifiers over multiple data sets. The Journal of Machine Learning Research, 7, 1\u201330.","journal-title":"The Journal of Machine Learning Research"},{"key":"5869_CR14","doi-asserted-by":"crossref","unstructured":"Domingos, P. (1999). Metacost: A general method for making classifiers cost-sensitive. In Proceedings of the fifth international conference on knowledge discovery and data mining (KDD\u201999) (pp. 155\u2013164).","DOI":"10.1145\/312129.312220"},{"key":"5869_CR15","unstructured":"Duin, R., Juszczak, P., Paclik, P., Pekalska, E., Ridder, D. D., Tax, D. M. J., & Verzakov, S. (2000). PRTools: A Matlab toolbox for pattern recognition. version 3, http:\/\/www.prtools.org"},{"key":"5869_CR16","first-page":"973","volume":"17","author":"C Elkan","year":"2001","unstructured":"Elkan, C. (2001). The foundations of cost-sensitive learning. Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 17, 973\u2013978.","journal-title":"Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence"},{"issue":"8","key":"5869_CR17","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","volume":"27","author":"T Fawcett","year":"2006","unstructured":"Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861\u2013874.","journal-title":"Pattern Recognition Letters"},{"issue":"1","key":"5869_CR18","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.patrec.2008.08.010","volume":"30","author":"C Ferri","year":"2009","unstructured":"Ferri, C., Hern\u00e1ndez-Orallo, H., & Modroiu, R. (2009). An experimental comparison of performance measures for classification. Pattern Recognition Letters, 30(1), 27\u201338.","journal-title":"Pattern Recognition Letters"},{"key":"5869_CR19","doi-asserted-by":"crossref","unstructured":"Frank, E., & Hall, M. (2001). A simple approach to ordinal classification. In Proceedings of the 12th European conference on machine learning (pp. 145\u2013156). Springer.","DOI":"10.1007\/3-540-44795-4_13"},{"issue":"2\u20133","key":"5869_CR20","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1023\/A:1007465528199","volume":"29","author":"N Friedman","year":"1997","unstructured":"Friedman, N., Geiger, D., & Goldszmidt, M. (1997). Bayesian network classifiers. Machine Learning, 29(2\u20133), 131\u2013163.","journal-title":"Machine Learning"},{"issue":"4","key":"5869_CR21","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1109\/TSMCC.2011.2161285","volume":"42","author":"M Galar","year":"2012","unstructured":"Galar, M., A\u00a0Fernandez, E. B., Bustince, H., & Herrera, F. (2012). A review on ensembles for the class imbalance problem: Bagging-, boosting-, and hybrid-based approaches. IEEE Transactions on Systems, Man, and Cybernetics: Part C\u2014Applications and Reviews, 42(4), 463\u2013484.","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Part C\u2014Applications and Reviews"},{"issue":"10","key":"5869_CR22","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1007\/s00500-008-0392-y","volume":"13","author":"S Garc\u00eda","year":"2009","unstructured":"Garc\u00eda, S., Fern\u00e1ndez, A., Luengo, J., & Herrera, F. (2009). A study of statistical techniques and performance measures for genetics-based machine learning: Accuracy and interpretability. Soft Computing, 13(10), 959\u2013977.","journal-title":"Soft Computing"},{"key":"5869_CR23","doi-asserted-by":"crossref","unstructured":"Garc\u00eda, V., Mollineda, R. A., & Sanchez, J. S. (2010). Theoretical analysis of a performance measure for imbalanced data. In Proceedings of the 20th international conference on pattern recognition (pp. 617\u2013620). IEEE.","DOI":"10.1109\/ICPR.2010.156"},{"issue":"3","key":"5869_CR24","doi-asserted-by":"publisher","first-page":"1344","DOI":"10.1214\/aos\/1069362752","volume":"25","author":"D Geiger","year":"1997","unstructured":"Geiger, D., & Heckerman, D. (1997). A characterization of the Dirichlet distribution through global and local parameter independence. The Annals of Statistics, 25(3), 1344\u20131369.","journal-title":"The Annals of Statistics"},{"issue":"10","key":"5869_CR100","doi-asserted-by":"publisher","first-page":"1578","DOI":"10.3390\/jcm8101578","volume":"8","author":"J Gordon","year":"2019","unstructured":"Gordon, J., & Lerner, B. (2019). Insights into ALS from a machine learning perspective. Journal of Clinical Medicine, 8(10), 1578.","journal-title":"Journal of Clinical Medicine"},{"issue":"5","key":"5869_CR25","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1016\/j.compbiolchem.2004.09.006","volume":"28","author":"J Gorodkin","year":"2004","unstructured":"Gorodkin, J. (2004). Comparing two k-category assignments by a k-category correlation coefficient. Computational Biology and Chemistry, 28(5), 367\u2013374.","journal-title":"Computational Biology and Chemistry"},{"key":"5869_CR26","doi-asserted-by":"crossref","unstructured":"Grossman, D., & Domingos, P. (2004). Learning Bayesian network classifiers by maximizing conditional likelihood. In Proceedings of the twenty-first international conference on machine learning (pp 361\u2013368). ACM.","DOI":"10.1145\/1015330.1015339"},{"key":"5869_CR27","unstructured":"Halbersberg, D., & Lerner, B. (2016). Learning a Bayesian network classifier by jointly maximizing accuracy and information. In Proceedings of the 22nd European conference on artificial intelligence (pp. 1638\u20131639). IOS Press."},{"key":"5869_CR28","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1016\/j.aap.2019.04.016","volume":"129","author":"D Halbersberg","year":"2019","unstructured":"Halbersberg, D., & Lerner, B. (2019). Young driver fatal motorcycle accident analysis by jointly maximizing accuracy and information. Accident Analysis and Prevention, 129, 350\u2013361.","journal-title":"Accident Analysis and Prevention"},{"issue":"2","key":"5869_CR29","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1023\/A:1010920819831","volume":"45","author":"DJ Hand","year":"2001","unstructured":"Hand, D. J., & Till, R. J. (2001). A simple generalisation of the area under the ROC curve for multiple class classification problems. Machine Learning, 45(2), 171\u2013186.","journal-title":"Machine Learning"},{"key":"5869_CR30","doi-asserted-by":"crossref","unstructured":"Heckerman, D. (1998). A tutorial on learning with Bayesian networks. In Learning in graphical models (pp 301\u2013354). Springer.","DOI":"10.1007\/978-94-011-5014-9_11"},{"key":"5869_CR31","first-page":"197","volume":"20","author":"D Heckerman","year":"1995","unstructured":"Heckerman, D., Geiger, D., & Chickering, D. (1995). Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning, 20, 197\u2013243.","journal-title":"Machine Learning"},{"issue":"4","key":"5869_CR32","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1016\/j.ijforecast.2006.03.001","volume":"22","author":"RJ Hyndman","year":"2006","unstructured":"Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679\u2013688.","journal-title":"International Journal of Forecasting"},{"key":"5869_CR33","doi-asserted-by":"crossref","unstructured":"Ide, J. S., & Cozman, F. G. (2002). Random generation of Bayesian networks. In Advances in artificial intelligence (pp. 366\u2013376). Springer.","DOI":"10.1007\/3-540-36127-8_35"},{"issue":"8","key":"5869_CR34","doi-asserted-by":"publisher","first-page":"e41882","DOI":"10.1371\/journal.pone.0041882","volume":"7","author":"G Jurman","year":"2012","unstructured":"Jurman, G., Riccadonna, S., & Furlanello, C. (2012). A comparison of MCC and CEN error measures in multi-class prediction. PLoS ONE, 7(8), e41882.","journal-title":"PLoS ONE"},{"issue":"2","key":"5869_CR35","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1016\/j.ijar.2011.10.006","volume":"53","author":"R Kelner","year":"2012","unstructured":"Kelner, R., & Lerner, B. (2012). Learning Bayesian network classifiers by risk minimization. International Journal of Approximate Reasoning, 53(2), 248\u2013272.","journal-title":"International Journal of Approximate Reasoning"},{"key":"5869_CR36","doi-asserted-by":"publisher","first-page":"942","DOI":"10.1016\/S0140-6736(10)61156-7","volume":"377","author":"M Kiernan","year":"2011","unstructured":"Kiernan, M., Vucic, S., Cheah, B., Turner, M., & Eisen, A. (2011). Amyotrophic lateral sclerosis. Lancet, 377, 942\u2013955.","journal-title":"Lancet"},{"key":"5869_CR37","unstructured":"Kontkanen, P., Myllym\u00e4ki, P., Silander, T., & Tirri, H. (1999). On supervised selection of bayesian networks. In Proceedings of the fifteenth conference on uncertainty in artificial intelligence (pp. 334\u2013342). Morgan Kaufmann Publishers Inc."},{"key":"5869_CR38","unstructured":"Labatut, V., & Cherifi, H. (2011). Accuracy measures for the comparison of classifiers. In Proceedings of the fifth international conference on information technology, ICIT."},{"issue":"3","key":"5869_CR39","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1111\/j.1467-8640.1994.tb00166.x","volume":"10","author":"W Lam","year":"1994","unstructured":"Lam, W., & Bacchus, F. (1994). Learning Bayesian belief networks: An approach based on the MDL principle. Computational Intelligence, 10(3), 269\u2013293.","journal-title":"Computational Intelligence"},{"key":"5869_CR40","unstructured":"Leray, P., & Francois, O. (2004). BNT structure learning package: Documentation and experiments. Tech Rep: Laboratoire PSI."},{"issue":"2","key":"5869_CR41","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1109\/TCBB.2007.070207","volume":"4","author":"B Lerner","year":"2007","unstructured":"Lerner, B., Yeshaya, J., & Koushnir, L. (2007). On the classification of a small imbalanced cytogenetic image database. IEEE Transactions on Computational Biology and Bioinformatics, 4(2), 204\u2013215.","journal-title":"IEEE Transactions on Computational Biology and Bioinformatics"},{"key":"5869_CR42","unstructured":"Lichman, M. (2013). UCI machine learning repository. http:\/\/archive.ics.uci.edu\/ml"},{"issue":"2","key":"5869_CR43","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1109\/21.229466","volume":"39","author":"XY Liu","year":"2009","unstructured":"Liu, X. Y., Wu, J., & Zhou, Z. H. (2009). Exploratory undersampling for class-imbalance learning. IEEE Transactions on Systems, Man, and Cybernetics: Part B\u2014Cybernetics, 39(2), 539\u2013550.","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Part B\u2014Cybernetics"},{"key":"5869_CR44","first-page":"51","volume":"33","author":"D Mitchell","year":"2007","unstructured":"Mitchell, D., & Borasio, G. (2007). Amyotrophic lateral sclerosis. Lancet, 33, 51\u201359.","journal-title":"Lancet"},{"issue":"2","key":"5869_CR45","first-page":"1024","volume":"33","author":"K Murphy","year":"2001","unstructured":"Murphy, K. (2001). The Bayes net toolbox for Matlab. Computing Science and Statistics, 33(2), 1024\u20131034.","journal-title":"Computing Science and Statistics"},{"key":"5869_CR46","unstructured":"OECD. (2006). Young drivers: The road to safety. Organization for Economic Co-operation and Development."},{"issue":"20","key":"5869_CR47","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1007\/s00180-007-0077-5","volume":"23","author":"R Piccareta","year":"2008","unstructured":"Piccareta, R. (2008). Classification trees for ordinal variables. Computational Statistics, 23(20), 407\u2013427.","journal-title":"Computational Statistics"},{"key":"5869_CR48","unstructured":"Provost, F. (2000). Machine learning from imbalanced data sets. In Proceedings of the AAAI workshop on imbalanced data sets (pp. 1\u20133)."},{"key":"5869_CR49","first-page":"445","volume":"98","author":"FJ Provost","year":"1998","unstructured":"Provost, F. J., Fawcett, T., & Kohavi, R. (1998). The case against accuracy estimation for comparing induction algorithms. Proceedings of the Fifteenth International Conference on Machine Learning, 98, 445\u2013453.","journal-title":"Proceedings of the Fifteenth International Conference on Machine Learning"},{"key":"5869_CR50","doi-asserted-by":"crossref","unstructured":"Ranawana, R., & Palade, V. (2006). Optimized precision\u2014A new measure for classifier performance evaluation. In IEEE Congress on evolutionary computation (pp. 2254\u20132261). IEEE.","DOI":"10.1109\/CEC.2006.1688586"},{"issue":"4","key":"5869_CR51","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1016\/j.ipm.2009.03.002","volume":"45","author":"M Sokolova","year":"2009","unstructured":"Sokolova, M., & Lapalme, G. (2009). A systematic analysis of performance measures for classification tasks. Information Processing and Management, 45(4), 427\u2013437.","journal-title":"Information Processing and Management"},{"issue":"6","key":"5869_CR52","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/0375-9601(90)90962-N","volume":"146","author":"M Suzuki","year":"1990","unstructured":"Suzuki, M. (1990). Fractal decomposition of exponential operators with applications to many-body theories and Monte Carlo simulations. Physics Letters A, 146(6), 319\u2013323.","journal-title":"Physics Letters A"},{"key":"5869_CR53","doi-asserted-by":"publisher","first-page":"705","DOI":"10.1016\/j.aap.2011.09.041","volume":"45","author":"T Toledo","year":"2012","unstructured":"Toledo, T., Lotan, T., Taubman-Ben-Ari, O., & Grimberg, E. (2012). Evaluation of a program to enhance young drivers\u2019 safety in Israel. Accident Analysis & Prevention, 45, 705\u2013710.","journal-title":"Accident Analysis & Prevention"},{"issue":"2","key":"5869_CR54","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1093\/comjnl\/11.2.185","volume":"11","author":"CS Wallace","year":"1968","unstructured":"Wallace, C. S., & Boulton, D. M. (1968). An information measure for classification. The Computer Journal, 11(2), 185\u2013194.","journal-title":"The Computer Journal"},{"issue":"10","key":"5869_CR55","doi-asserted-by":"publisher","first-page":"1388","DOI":"10.1109\/TKDE.2009.187","volume":"22","author":"M Wasikowski","year":"2010","unstructured":"Wasikowski, M., & Chen, X. W. (2010). Combating the small sample class imbalance problem using feature selection. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1388\u20131400.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"5","key":"5869_CR56","doi-asserted-by":"publisher","first-page":"3799","DOI":"10.1016\/j.eswa.2009.11.040","volume":"37","author":"JM Wei","year":"2010","unstructured":"Wei, J. M., Yuan, X. J., Hu, Q. H., & Wang, S. Q. (2010). A novel measure for evaluating classifiers. Expert Systems with Applications, 37(5), 3799\u20133809.","journal-title":"Expert Systems with Applications"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-020-05869-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-020-05869-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-020-05869-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,28]],"date-time":"2021-02-28T01:06:41Z","timestamp":1614474401000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-020-05869-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2,28]]},"references-count":57,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2020,5]]}},"alternative-id":["5869"],"URL":"https:\/\/doi.org\/10.1007\/s10994-020-05869-5","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,2,28]]},"assertion":[{"value":"24 July 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 May 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 January 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}