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LDR01630cmm u2200385Mu 4500
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003OCoLC
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006m d
007cr cnu---unuuu
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020 ▼a 9780309695091 ▼q (electronic bk.)
020 ▼a 0309695090 ▼q (electronic bk.)
020 ▼a 9780309695077
020 ▼a 0309695074
035 ▼a 3517607 ▼b (N$T)
035 ▼a (OCoLC)1356004447
040 ▼a EBLCP ▼b eng ▼c EBLCP ▼d OCLCO ▼d OCLCQ ▼d N$T ▼d 248032
049 ▼a MAIN
050 4 ▼a HV6545
08204 ▼a 362.28 ▼2 23/eng/20231010
1102 ▼a National Academies of Sciences, Engineering, and Medicine (U.S.)
24510 ▼a Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide ▼h [electronic resource] : ▼b Proceedings of a Workshop.
260 ▼a Washington, D.C. : ▼b National Academies Press, ▼c 2023.
300 ▼a 1 online resource (97 p.)
5880 ▼a Print version record.
590 ▼a Added to collection customer.56279.3
650 0 ▼a Suicide ▼x Prevention ▼v Congresses.
7001 ▼a Nass, Sharyl J.
7001 ▼a Pool, Robert.
7001 ▼a Amankwah, Francis.
77608 ▼i Print version: ▼a National Academies of Sciences, Engineering, and Medicine. ▼t Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide. ▼d Washington, D.C. : National Academies Press, 2023 ▼z 9780309695077
85640 ▼3 EBSCOhost ▼u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3517607
938 ▼a EBSCOhost ▼b EBSC ▼n 3517607
990 ▼a 관리자
994 ▼a 92 ▼b N$T