ライフサイエンスコーパス: fraud

1 organic food market susceptible to attempted fraud.

2 titative evidence on the extent of electoral fraud.

3 and T. melanosporum and thus avoid possible fraud.

4 erent origins, which may provide evidence of fraud.

5 ally underlie older adults' vulnerability to fraud.

6 at research institutions investigate alleged fraud.

7 the electoral process, and the prevention of fraud.

8 ty of rabbit meat makes it a target for food fraud.

9 ication of Iberian hams and for detection of fraud.

10 y recognizing samples that could represent a fraud.

11 , alleging widespread and unparalleled voter fraud.

12 d by cheaper raw materials resulting in food fraud.

13 s susceptible to economically motivated food fraud.

14 n how voter ID laws affect voter turnout and fraud.

15 be considered to safeguard customers against fraud.

16 s crucial for traceability and fighting food fraud.

17 oods, encouraging financially motivated food fraud.

18 strialized foods to detect adulterations and fraud.

19 ubfields are equally targeted for scientific fraud.

20 of spreading fake information or committing fraud.

21 mplexity and economic value predispose it to fraud.

22 re frequent targets and victims of financial fraud.

23 re being developed to uncover these types of fraud.

24 as specific markers to detect potential food fraud.

25 global popularity, making them vulnerable to fraud.

26 ht after by consumers but also prone to food fraud.

27 indication, making it a potential target for fraud.

28 hat allow the identification of this type of fraud.

29 ssions-that facilitate systematic scientific fraud.

30 inimizing stigma and reducing incentives for fraud.

31 demand leading to an increased risk of food fraud.

32 l Indication (PGI) and are subject to origin fraud.

33 popular herb, is particularly vulnerable to fraud.

34 l origin of single-origin coffee and prevent fraud.

35 ical origin, making hazelnuts susceptible to fraud.

36 ntial to guarantee their quality and prevent fraud.

37 s to ensure consumer health and prevent food fraud.

38 rticularly vulnerable to systematic research fraud.

39 perties, which is highly susceptible to food fraud.

40 e most likely foods to be the target of food fraud.

41 more than tinker at the edges of scientific fraud.

42 ... they have also changed the very form of fraud.

43 t online behaviours(21,22) such as financial fraud.

44 aries more than 100-fold, it is a target for fraud.

45 to disguise spoilage, thus resulting in food fraud.

46 tential for screening and detection of wheat fraud.

47 ocedures to detect and ultimately deter food fraud.

48 s become a common source of adulteration and fraud.

49 der to certify their origin and prevent food fraud.

50 ndustrial processes and to deter intentional fraud.

51 e mean to verify traceability and counteract fraud.

52 d of potential use for the detection of food fraud.

53 oped to compare their ability to detect food fraud.

54 s not covered by the NCD may be construed as fraud.

55 ion of food origin is relevant to avoid food fraud.

56 and rapid tool in the fight against saffron fraud.

57 n olive oil (EVOO) is subjected to different frauds.

58 od products are subject to adulterations and frauds.

59 ducts repackaging constitute the most common frauds.

60 od fingerprint analyses to detect commercial frauds.

61 free-range chickens have been the target of frauds.

62 eling represents one of the major commercial frauds.

63 od supply chains to species mislabelling and fraud [1,2].

64 to misconduct, including fraud or suspected fraud (43.4%), duplicate publication (14.2%), and plagia

65 appropriate contact with patients (10%), and fraud (9%).

66 With the increased risk of wine fraud, a rapid and simple method for wine authentication

67 There are chances of food fraud about the claim of being gluten-free food items.

68 winner, fraud prevalence and beneficiary of fraud-accurately accounted for this partisan asymmetry,

69 , however, reports of coordinated scientific fraud activities have increased.

70 it could be used as a tool to check possible fraud, adulteration or non-compliance to the law.

71 nal farming as well as the detection of food fraud/adulteration, has been a rapidly growing field ove

72 rvice providers, especially in screening for fraud against the national medical insurance schemes and

73 These frauds all have an analytical component, and research te

74 Food fraud, along with many challenges to the integrity and s

75 requirements, and concerns about health care fraud also limit its use.

76 ment of apricot products susceptible to food fraud, an environmentally friendly, simple and cost-effe

77 herry tomato of Pachino (Sicily, Italy) from frauds, an alternative method, which includes chemometri

78 simple technologies will revolutionize food fraud analysis.

79 To protect consumers from food fraud, analytical methods to differentiate such juices f

80 .3%) admitted to having committed scientific fraud and 54 (21.3%) reported having witnessed or suspec

81 In recent years, health care fraud and abuse have become major issues, in part becaus

82 cement authorities responsible for combating fraud and abuse have focused greater attention on the sc

83 Enforcement of health care fraud and abuse laws has become increasingly commonplace

84 failure, $81.4 billion to $91.2 billion; and fraud and abuse, $22.8 billion to $30.8 billion.

85 g failure, $230.7 billion to $240.5 billion; fraud and abuse, $58.5 billion to $83.9 billion; and adm

86 reatment or low-value care, pricing failure, fraud and abuse, and administrative complexity.

87 nistrative complexity, pricing failures, and fraud and abuse--the sum of the lowest available estimat

88 en without decreasing the ability to prevent fraud and abuse.

89 dustries because of the increasing number of fraud and adulteration attempts to the market products.

90 ed value, it is also a prime target for food fraud and adulteration.

91 to control specifications and regarding food fraud and allergenic potential.

92 ensure adequate labelling and minimize food fraud and allergenic potential.

93 To tackle food fraud and authentication, non-destructive techniques are

94 lity of foods, provide new methods to combat fraud and be useful tools in our arsenal against bioterr

95 ded to protect the craft brew market against fraud and counterfeit.

96 Food fraud and counterfeiting involves all types of foods, fe

97 ations of origin, thereby helping to prevent fraud and ensure product traceability.

98 ication of these species helps to avoid food fraud and health problems.

99 fication protocol for olive oils can lead to fraud and health risks.

100 ed 4 reports between 2009 and 2011 detailing fraud and misapplication of Medicare funds for powered w

101 The detection of meat fraud and mislabeling in processed meat products is a ra

102 Species fraud and product mislabelling in processed food, albeit

103 The results obtained will help to avoid fraud and protect the European Designation of Origin 'Me

104 regulation, growing concerns with scientific fraud and publication malpractice, and the stresses and

105 an Commission (EC) Knowledge Centre for Food Fraud and Quality is charged with the provision of scien

106 MIT) who was accused by the US government of fraud and questionable connections to Chinese entities.

107 arch on the vulnerability of older adults to fraud and scams relies almost exclusively on self-report

108 Financial fraud and scams targeting older adults are on the rise a

109 hout cognitive impairment, are vulnerable to fraud and scams.

110 enhance the inherent vulnerability of FMP to fraud and stability.

111 nt of publications revealing suspected trial fraud and/or randomization failure.

112 up analytical strategies for detecting food frauds and adulterations by monitoring selected componen

113 In recent years, food frauds and adulterations have increased significantly.

114 c focus on their use for unmasking potential frauds and adulterations.

115 for food quality control, allowing detecting frauds and enabling faster and reliable analyzes.

116 of nonconsensual intimate imagery, financial fraud, and disinformation campaigns.

117 se in nonconsensual pornography, large-scale fraud, and disinformation campaigns.

118 adults are disproportionately vulnerable to fraud, and federal agencies have speculated that excessi

119 licy making of EC services dealing with food fraud, and the creation of expert networks with the comp

120 gainst a list of visa holders to detect visa fraud, and visitors entering the U.S. are checked agains

121 he traditional methodologies to monitor this fraud are based on the analysis of caseinomacropeptide.

122 lated (IUU) fishing and seafood supply chain fraud are multifaceted problems that demand multifaceted

123 Detection and prevention of fish food fraud are of ever-increasing importance, prompting the n

124 tentially be used to detect adulteration and frauds, as well as to differentiate rums by aging time.

125 be viable for dealing with extensive saffron frauds at a minimum level of 20% (w/w).

126 Thus, how older adults truly respond to fraud attempts remains unclear.

127 olour and has been successfully used in meat fraud authentication.

128 hod for comparing models used to detect food fraud based on stable isotopes and trace element (SITE)

129 curate methodology of detecting social media fraud based on the combination of sophisticated sequence

130 mericans during the 2020 vote count, testing fraud belief updates given hypothetical election outcome

131 ing again increased confidence and decreased fraud beliefs but only when the forewarning was omitted,

132 Participants' fraud beliefs increased when their preferred candidate l

133 ly increased election confidence and reduced fraud beliefs, with prebunking showing somewhat more dur

134 Even minor vulnerabilities can result in fraud, business disruptions, and loss of visibility.

135 on of olive oil is not only a major economic fraud but can also have major health implications for co

136 n order to avoid mislabelling and commercial fraud, but also to address food safety issues and to com

137 e plant oils have become susceptible to food fraud by adulteration with cheaper vegetable oils, compr

138 ted having witnessed or suspected scientific fraud by someone in their department in the past 5 y.

139 results of this study clearly indicate that frauds by adding grapefruit juice to orange juice can be

140 The results indicated that frauds by adding pumpkin to apricot products can be dete

141 such as corruption, tax evasion or political fraud, can compromise individual intrinsic honesty.

142 s (difference, 0.002 [95% CI, 0.002-0.003]), fraud cases (eg, animal charity difference, 0.0003 [95%

143 Eight fraud cases included financial awards (median: $2 335 91

144 Fifteen cases involved fraud claims, primarily Medicare fraud (n = 8) and impro

145 sence of saccharin in non-diet beverages - a fraud commonly used to replace more expensive sucrose -

146 heir geographical origin is known as a major fraud concern of the sector.

147 This fraud consisted of injecting solutions of non-meat ingre

148 The problem of fraud continues to plague the wine industry, and detecti

149 Organic food frauds continuously threaten consumer trust in the agri-

150 ound-roasted coffee, thus acting as a coffee fraud control and prevention tool.

151 heir application as diagnostic tools in food fraud control.

152 The detection of potential fraud could be improved by using the tools linking the c

153 Most forms of document and branded-product fraud could be rendered obsolete by use of this code.

154 the industry faces pressing issues like food fraud, deforestation, and climate change.

155 erformance, with the LLM achieving up to 99% fraud detection accuracy.

156 and reliable for verifying authenticity and fraud detection in BHH.

157 was to develop a quick and cheap method for fraud detection in egg labels according to the four lega

158 r honey authentication, quality control, and fraud detection in the food industry.

159 scalable, and precise model of social media fraud detection is required.

160 Existing fraud detection methods are largely manual, time-consumi

161 The limit of fraud detection of lower grade oils in EVOO was 2% when

162 followed by breast mammogram and credit card fraud detection tasks.

163 l automation, manufacturing, cyber security, fraud detection, and drug research, among others.

164 erest owing to its applications in security, fraud detection, and system monitoring.

165 scopy for alcohol content quantification and fraud detection, eliminating the need for chemical reage

166 PLS-DA/OFF model achieved 97.3 % accuracy in fraud detection, while the iSPA-PLS-DA/OFF model reached

167 nmental agencies, especially in the field of fraud detection.

168 ficiently significant so as to apply them to fraud detection.

169 ine, particularly for quality assessment and fraud detection.

170 ect success rate was achieved for rice flour fraud detection.

171 -ICP-MS, making it a realistic tool for food fraud detection.

172 ed for analytical instrumentation methods in fraud detection.

173 nd Large Language Models (LLMs) to transform fraud detection.

174 sed for coffee provenance authentication and fraud detection.

175 ed further to determine their usefulness for fraud detection.

176 Notably, greater worry about prosecution for fraud did not affect physicians' use of these tactics (P

177 ts is not always straightforward due to food fraud, differing labelling regulations, naming inconsist

178 presence mainly exist in literature, however fraud due to trimming has not been reported.

179 graphical origin, making them susceptible to fraud, especially counterfeit claims regarding their pro

180 nt findings can help in improving commercial fraud fight, extending the possibility to authenticate f

181 arkable ability to discern instances of food fraud, food spoilage and food safety concerns.

182 Honey is one of the most frequently frauded foods due to the high market price of certain ki

183 Species substitution is a form of seafood fraud for the purpose of economic gain.

184 dates for potential markers to detect coffee fraud, found exclusively in one type of adulterant: coff

185 Tea (Camellia sinensis) fraud has been frequently identified and involves tamper

186 of scientific articles retracted because of fraud has increased approximately 10-fold since 1975.

187 od authenticity studies, like dairy products fraud, holding promise for the discovery of potential au

188 of messages countering claims of widespread fraud: (i) retrospective corrections from credible sourc

189 ed to assess rice flour authenticity through fraud identification.

190 ducts makes food traceability a priority for frauds identification and quality certification.

191 eat help in the field of quality control and frauds identification.

192 nited States, baseless claims about election fraud in 2020 by the losing presidential candidate, Dona

193 ion of hazelnut oil into olive oil, a common fraud in food industry.

194 The contrast of fraud in international trade is a crucial task of modern

195 sed for testing the global supply chains for fraud in many different forms of herbs.

196 Food fraud in olive oil is a major concern for consumers and

197 sed to characterise wines and to detect wine fraud in other countries but have not been extensively t

198 play an important role in the fight against fraud in pharmaceuticals and many other products.

199 nterest of researchers in investigating this fraud in recent years.

200 es for the detection of oil adulteration and fraud in the food and feed industry.

201 recent years due to the rising incidence of fraud in the food industry.

202 Fraud in the food supply system will be exacerbated by s

203 Fraud in the global food supply chain is becoming increa

204 Food fraud in the meat industry threatens consumer trust, mar

205 to a previous underestimation of the role of fraud in the ongoing retraction epidemic.

206 s may be helpful predictive markers to limit fraud in these species.

207 lassify Sudan Red, starch and metanil yellow fraud in turmeric powder nondestructively.

208 al origin, and may be useful in detection of frauds in berry-based seed-containing product.

209 new isobaric lignans is suggested to reveal frauds in commercial extra-Virgin Olive Oils.

210 velop statistical tools for the detection of frauds in customs declarations that rely on the Newcomb-

211 al feed additive, ractopamine to combat food frauds in meat samples.

212 to classify Iberian ham, to detect possible frauds in their labelling.

213 Due to increasing number of food fraud incidents, there is an inherent need for the devel

214 Common frauds include blending with other cheaper non-olive oil

215 of global food supply chains and trade, food fraud, including adulteration of high value foods with c

216 hniques are used to identify and detect food fraud, including spectroscopy, chromatography, DNA barco

217 wine market has always faced the problem of fraud, including the addition of exogenous sugar solutio

218 In the course of recent health care fraud investigations against TAP Pharmaceuticals (Lake F

219 Beverage fraud involving counterfeiting of brand spirits is an in

220 Fraud involving fish products is regularly reported and

221 Electoral fraud is a widespread phenomenon, especially outside the

222 organic bananas, the detection of fertilizer fraud is much more complex.

223 nalytical approaches to be used against food fraud is necessary.

224 Food fraud is perpetrated with increasing frequency along the

225 The most frequent fraud is practiced in staple food commodities like cerea

226 While the detection of pesticide fraud is routinely controlled by detecting pesticide res

227 Food fraud is still a recurrent practice throughout food supp

228 etime or pattern masking are advantageous if fraud is to be deterred.

229 such an integrated system for combating food fraud is under development.

230 Food fraud is widespread nowadays in the food products supply

231 gard olive oil as highly susceptible to food fraud, largely due to its substantial economic worth.

232 that are generally prohibited by health care fraud laws are false claims, kickbacks, and self-referra

233 tes the scope and characteristics of qui tam fraud litigation and the whistleblowers who animate this

234 This type of fraud may lower consumers' confidence as inferior produc

235 utine tools in control laboratories for food fraud monitoring.

236 es involved fraud claims, primarily Medicare fraud (n = 8) and improper billing (n = 4); among these,

237 ast report from the European Union (EU) Food Fraud Network, olive oil tops the list of the most notif

238 Seafood fraud - often involving substitution of one species by a

239 f Moscow to estimate the effect of electoral fraud on the outcome of the Russian parliamentary electi

240 gle Scholar to examine instances of citation fraud on the platform.

241 S. scombrus and may aid in the prevention of fraud or mislabelling in mackerel products.

242 traded saffron that suffers various types of fraud or mislabelling.

243 shares of the market, and the impact of tax fraud or retailer non-compliance with minimum unit price

244 It was an honest mistake, not fraud or scientific misconduct.

245 as chemical analysis to find indications for fraud or spoilage of fine and rare wines as well as othe

246 s were attributable to misconduct, including fraud or suspected fraud (43.4%), duplicate publication

247 evidence of environmental impacts from food fraud, our results also highlight the current challenges

248 s of relevant clinical information to detect fraud patterns and inconsistencies.

249 ct, as shown by a case history of scientific fraud perpetrated by Eric Poehlman, PhD.

250 ratio as a powerful tool to unveil olive oil fraud practices and fat manipulation.

251 The rise of food fraud practices, affecting a wide variety of goods and t

252 Fraud, pre-analytical and analytical limitations, and in

253 of beliefs-beliefs in the true vote winner, fraud prevalence and beneficiary of fraud-accurately acc

254 be easily used to assist quality control and fraud prevention in the egg industry.

255 iques for black pepper authentication toward fraud prevention.

256 authenticity biomarkers detection useful in frauds prevention.

257 ble to apply the described workflows to food fraud problems, with an objective of identifying key mar

258 Conclusion: Scientific fraud, publication bias, and honorary authorship appear

259 icine scientists' experience with scientific fraud, publication bias, and honorary authorship.

260 Food fraud raises significant concerns to consumer health and

261 mer trust, this strategy addresses potential fraud related to geographical origin.

262 d those who liked or shared tweets promoting fraud-related conspiracy theories were slightly less lik

263 ld serve as a reference for detecting salmon fraud relating to wild or farmed production and expand t

264 Effective protection against fraud requires severe controls based on accurate analyti

265 Exposing such food frauds requires a reliable analytical method.

266 This approach significantly enhances fraud resistance and enables objective quality assessmen

267 ticity are increasing recently, due to great fraud scandals.

268 vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtos

269 ors have aggressively prosecuted health care fraud since the early 1990s, leading to billions of doll

270 A analysis has helped to combat this type of fraud some of the methods currently in use are time-cons

271 s demonstrate the system's ability to detect fraud such as inflated costs, unnecessary treatments, an

272 te analytical techniques in identifying food fraud, such as principal component analysis, partial lea

273 As the full extent of the fraud surrounding the generation of patient-specific emb

274 Recently, fraud suspicion on lingonberries-based products has been

275 The adulteration of edible fats is a kind of fraud that impairs the physical and chemical features of

276 ral qui tam litigation targeting health care fraud that was resolved between 1996 and 2005 from the U

277 ty were mainly in 900-1700 cm(-1), while for fraud the features were more dispersed.

278 ped over the years for the detection of meat fraud, the aim of the present review is to take stock of

279 or effectively and efficiently fighting food fraud, the Centre together with the competent authoritie

280 Putting aside deliberate fraud, there is evidence that a major contributor to lac

281 Systematic fraud threatens the integrity of science, with paper and

282 hat enable the entities promoting scientific fraud to evade interventions.

283 tle-blowers," and a change in the concept of fraud to include an emerging concern about quality of ca

284 The fight against fraud to safeguard high-quality productions requires an

285 aspects of quality and detection of possible frauds to ensure the integrity of the food.

286 ally focus on structured data and predefined fraud types, offering limited adaptability and analytica

287 nter misinformation about voter and election fraud using data from the US and Brazil.

288 s a new approach to detect and quantify this fraud using the fatty acid profiles of milk and whey.

289 nd reliable method for detecting milk powder frauds using cheese whey.

290 reign matters has been a constant concern in fraud verification, especially because it is difficult t

291 Our results suggest that the extent of the fraud was sufficient to have had a substantial impact on

292 -targeted analysis for the detection of food frauds were analyzed employing discriminant analysis and

293 has not been studied yet and it can become a fraud when it is used to simulate the effect of a longer

294 ps and prawns are especially subject to food fraud, which has consequences not only on the economy bu

295 represent an effective tool to prevent food fraud, which is crucial for meat derived products with a

296 Addressing food safety and detecting food fraud while fulfilling greenness requisites for analysis

297 publican Party-claim that they prevent voter fraud, while Democratic opponents denounce the dispropor

298 Geographic origin is by far the fraud with the most attention.

299 in tissue that could aid in the discovery of fraud within the food industry.