{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T08:24:58Z","timestamp":1787300698257,"version":"build-2736575974"},"reference-count":21,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"vor","delay-in-days":232,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP21K14949"],"award-info":[{"award-number":["JP21K14949"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Animal Science Journal"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Prediction of calving among cattle based on body temperature is used to prevent calving accidents. However, conventional threshold\u2010based methods often miss or misdetect signs of calving. We quantitatively compared a machine learning\u2010based model with conventional threshold\u2010based methods for calving prediction using vaginal temperature data from wearable devices. Vaginal temperature was recorded at 5\u2010min intervals from approximately 7\u2009days before the expected calving date until parturition in beef (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200977) and dairy cattle (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200978). Twenty\u2010six time\u2010series features were extracted, and a machine learning\u2010based calving prediction model was developed using gradient\u2010boosted decision trees. The model predicting calving within 24\u2009h achieved 84.4% and 94.9% sensitivity and 60.2% and 56.1% precision in beef and dairy cattle, respectively, compared with 70.1% and 76.9% sensitivity and 38.3% and 51.7% precision for a conventional threshold\u2010based model using fixed threshold values derived from previous literature. Furthermore, the model predicting calving within 12\u2009h achieved performance comparable to that of the 24\u2010h model (81.8% and 84.6% sensitivity; 50.0% and 42.3% precision, respectively), suggesting the feasibility of customizable alert timing across multiple time windows. Further improvements, including larger datasets and refined feature engineering and model optimization, are needed to reduce missed and false detections.\n                  <\/jats:p>","DOI":"10.1111\/asj.70235","type":"journal-article","created":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T07:56:30Z","timestamp":1787298990000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of Approaches to Cattle Calving Prediction Based on Vaginal Temperature: Machine Learning\u2010Versus Threshold\u2010Based Models"],"prefix":"10.1111","volume":"97","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3389-3610","authenticated-orcid":false,"given":"Masafumi","family":"Miwa","sequence":"first","affiliation":[{"name":"Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO)  Nasushiobara Tochigi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaiyu","family":"Kubota","sequence":"additional","affiliation":[{"name":"Institute of Livestock and Grassland, National Agriculture and Food Research Organization (NARO) Science  Tsukuba Ibaraki Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3403-7568","authenticated-orcid":false,"given":"Tsumugi","family":"Yoshiyama","sequence":"additional","affiliation":[{"name":"Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO)  Nasushiobara Tochigi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3958-6710","authenticated-orcid":false,"given":"Miki","family":"Sakatani","sequence":"additional","affiliation":[{"name":"Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization (NARO)  Nasushiobara Tochigi Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,21]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.anireprosci.2004.04.046h"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.3168\/jds.2011\u20104484"},{"key":"e_1_2_10_4_1","doi-asserted-by":"crossref","unstructured":"Chen T. andC.Guestrin.2016. \u201cXGBoost: A Scalable Tree Boosting System.\u201d In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '16). Association for Computing Machinery New York NY USA 785\u2013794.https:\/\/doi.org\/10.1145\/2939672.2939785.","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.3168\/jds.2014\u20109289"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1013203451"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1262\/jrd.2022\u2010107"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.3168\/jds.2019\u201017689"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.3390\/ani12162095"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0378\u20104320(02)00092\u20101"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tvjl.2018.08.006"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.2527\/1997.7592526x"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.3168\/jds.2015\u201010057"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inpa.2017.10.001"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.theriogenology.2018.02.009"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tvjl.2015.05.006"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.theriogenology.2017.09.033"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.theriogenology.2021.07.002"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.theriogenology.2018.01.016"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.3168\/jds.2011\u20104436"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.4142\/jvs.2011.12.2.177"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.3390\/ani12152006"}],"container-title":["Animal Science Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/asj.70235","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/asj.70235","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/asj.70235","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T07:56:31Z","timestamp":1787298991000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/asj.70235"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":21,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["10.1111\/asj.70235"],"URL":"https:\/\/doi.org\/10.1111\/asj.70235","archive":["Portico"],"relation":{},"ISSN":["1344-3941","1740-0929"],"issn-type":[{"value":"1344-3941","type":"print"},{"value":"1740-0929","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"2026-03-06","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-06","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70235"}}