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| Status | Merged (Changelog #3001410) |
| Editor | crossref-bot |
| Description | Automated import of Crossref DOI metadata, harvested from REST API |
Extra Metadata (raw JSON)
agent |
fatcat_tools.CrossrefImporter
|
git_rev |
v0.3.1-43-g44c2329
|
Release Edit Diffs (50)
Revision:
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Revision:
497f548e-315e-4c75-afec-2467ef1ebb96
--- (created)
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Revision:
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Revision:
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--- (created)
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+authors = [ "Fletcher S.G.",]
+volume-title = "Diagnosing Speech Disorders From Cleft Palate."
+[[refs]]
+index = 6
+key = "bibr7-1545-1569_2003_040_0040_consof_2.0.co_2"
+year = 1970
+container_name = "Cleft Palate J."
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+container_name = "Cleft Palate Craniofac J."
+locator = "106"
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+authors = [ "Gildersleeve-Neuman C.E.",]
+doi = "10.1597/1545-1569(2001)038<0106:nsiniw>2.0.co;2"
+volume = "38"
+[[refs]]
+index = 9
+key = "bibr10-1545-1569_2003_040_0040_consof_2.0.co_2"
+year = 1992
+container_name = "Cleft Palate J."
+locator = "346"
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+[refs.extra]
+authors = [ "Hardin M.A.",]
+doi = "10.1597/1545-1569(1992)029<0346:cbnsal>2.3.co;2"
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+year = 1995
+container_name = "Cleft Palate Craniofac J."
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+doi = "10.1597/1545-1569_1995_032_0145_ndohat_2.3.co_2"
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+key = "bibr14-1545-1569_2003_040_0040_consof_2.0.co_2"
+year = 1991
+container_name = "J Speech Hear Res."
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+authors = [ "Seaver E.J.",]
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+key = "bibr15-1545-1569_2003_040_0040_consof_2.0.co_2"
+year = 1988
+container_name = "SPSS-X User's Guide."
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+authors = [ "SPSS-X.",]
+volume-title = "SPSS-X User's Guide."
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+year = 1999
+container_name = "Cleft Palate Craniofac J."
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+[refs.extra]
+authors = [ "Watterson T.",]
+doi = "10.1597/1545-1569_1999_036_0243_eoslon_2.3.co_2"
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Revision:
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--- (created)
+++ /release/rev/dbaefe3a-dbd5-4b44-8307-5faffe052344.toml
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+title = "Improved Diabetes Care Management Through a Text-Message Intervention for Low-Income Patients: Mixed-Methods Pilot Study (Preprint)"
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+[[contribs]]
+index = 2
+raw_name = "Stephen M Shortell"
+given_name = "Stephen M"
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+doi = "10.1007/s00125-009-1559-5"
+[[refs]]
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+[refs.extra]
+doi = "10.1016/s0140-6736(09)60697-8"
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+content = "<sec>\n <title>BACKGROUND</title>\n <p>Diabetes is a major contributor to global death and disability. Text-messaging interventions hold promise for improving diabetes outcomes through better knowledge and self-management.</p>\n </sec>\n <sec>\n <title>OBJECTIVE</title>\n <p>The aim of this study was to examine the implementation and impact of a diabetes text-messaging program targeted primarily for low-income Latino patients receiving care at 2 federally qualified health centers (FQHCs).</p>\n </sec>\n <sec>\n <title>METHODS</title>\n <p>A mixed-methods, quasi-experimental research design was employed for this pilot study. A total of 50 Spanish or English-speaking adult patients with diabetes attending 2 FQHC sites in Los Angeles from September 2015 to February 2016 were enrolled in a 12-week, bidirectional text-messaging program. A comparison group (n=160) was constructed from unexposed, eligible patients. Demographic data and pre/post clinical indicators were compared for both the groups. Propensity score weighting was used to reduce selection bias, and over-time differences in clinical outcomes between groups were estimated using individual fixed-effects regression models. Population-averaged linear models were estimated to assess differential effects of patient engagement on each clinical indicator among the intervention participants. A sample of intervention patients (n=11) and all implementing staff (n=8) were interviewed about their experiences with the program. Qualitative data were transcribed, translated, and analyzed to identify common themes.</p>\n </sec>\n <sec>\n <title>RESULTS</title>\n <p>The intervention group had a mean glycated hemoglobin (HbA1c) reduction of 0.4 points at follow-up, relative to the comparison group (P=.06). Patients who were more highly engaged with the program (response rate ≥median of 64.5%) experienced a 2.2 point reduction in HbA1c, relative to patients who were less engaged, controlling for demographic characteristics (P<.001). Qualitative analyses revealed that many participants felt supported, as though \"someone was worrying about [their] health.\" Participants also cited learning new information, setting new goals, and receiving helpful reminders. Staff and patients highlighted strategies to improve the program, including incorporating patient responses into in-person clinical care and tailoring the messages to patient knowledge.</p>\n </sec>\n <sec>\n <title>CONCLUSIONS</title>\n <p>A diabetes text-messaging program provided instrumental and emotional support for participants and may have contributed to clinically meaningful improvements in HbA1c. Patients who were more engaged demonstrated greater improvement. Program improvements, such as linkages to clinical care, hold potential for improving patient engagement and ultimately, improving clinical outcomes.</p>\n </sec>"
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Revision:
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Revision:
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+container_name = "Journal of Entomology and Zoology Studies"
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+[refs.extra]
+authors = [ "Christudhas A.",]
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+doi = "10.1046/j.1365-2672.2000.00841.x"
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+container_name = "Entomology"
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+authors = [ "Feng H. Q.",]
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+year = 2008
+container_name = "Boletin De Malaiologia Y Salud Ambiental"
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+[refs.extra]
+authors = [ "Gamboa M.",]
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+doi = "10.3390/ijms13032863"
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+year = 1999
+container_name = "POPGENE version 1.32. Microsoft Window-based Freeware for population genetic analysis"
+
+[refs.extra]
+authors = [ "Yeh F.",]
+volume-title = "POPGENE version 1.32. Microsoft Window-based Freeware for population genetic analysis"
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Revision:
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+title = "الأدب والبيئة ومسألة ما بعد الإنسان"
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+index = 0
+raw_name = "Abd Al-Rahman Mohammad Teama"
+given_name = "Abd Al-Rahman Mohammad"
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Revision:
e856e3fe-40fc-4f33-88d7-290d7f48cc28
--- (created)
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+title = "DFR – A New Model to Identifying Loyal Tourists on the Destination"
+work_id = "hau7omwmivbrveoern5ab3rrs4"
+container_id = "c7nfbt3imrcrpl5ll33aznuhxi"
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+publisher = "SC ASERS SRL"
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+[[contribs]]
+index = 0
+raw_name = "Shahrzad SEDAGHAT"
+given_name = "Shahrzad"
+surname = "SEDAGHAT"
+role = "author"
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+seq = "first"
+[[contribs]]
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+raw_name = "Mohammad Reza DEHGHANI ZADEH"
+given_name = "Mohammad Reza"
+surname = "DEHGHANI ZADEH"
+role = "author"
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+[contribs.extra]
+seq = "first"
+[[contribs]]
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+raw_name = "Vahid AMIRI"
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+content = "<jats:p>Regarding the increasing tendency to travel in recent years, many cities offer more amusement plans to have the tourists visit them again. The importance of these plans is due to maintaining the current tourists, but not attracting the new ones. Hence, recognizing loyal tourists can reduce the expenses and flourish the tourism. Accordingly, in this research, we have attempted to develop a new model based on data mining techniques to reconnoiter loyal tourists more accurately. The presented model is named DFR and is based on the development of the well-known model RFM. In addition to DFR model, the Imperialist Competitive Algorithm (ICA) has been used to cluster the tourists. The DFR model was implemented on 1100 tourists visiting Shiraz between 2013 and 2015, show that this model has a higher accuracy than other existing models and has identified loyal tourists more precisely.</jats:p>"
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Revision:
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+title = "A Study on CBR Behaviour of Waste Pet Strip Reinforced Stone Dust"
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+raw_name = "Abdhesh Kumar Sinha"
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+[[contribs]]
+index = 2
+raw_name = "Anil Kumar Choudhary"
+given_name = "Anil Kumar"
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+[[refs]]
+index = 0
+key = "36_CR2"
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+[refs.extra]
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