cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57745/ha8o6g
title: Q236401001_incertitude_datasheet.pdf
DOI: 10.57745/ikogxj
title: Q245029000_incertitude_datasheet.pdf
DOI: 10.57745/lpyjpl
title: Q240291001_incertitude_datasheet.pdf
DOI: 10.57745/o1rwpl
title: Q241431500_incertitude_datasheet.pdf
DOI: 10.57745/ritis6
title: Q254431001_incertitude_datasheet.pdf
DOI: 10.57745/wk5bea
title: Q235401001_incertitude_datasheet.pdf
DOI: 10.57745/zen7mv
title: Q258461001_incertitude_datasheet.pdf
DOI: 10.57745/c5a9xl
title: Q312001002_incertitude_datasheet.pdf
DOI: 10.57745/c8c10j
title: Q305401001_incertitude_datasheet.pdf
DOI: 10.57745/cw79pm
title: Q266025000_incertitude_datasheet.pdf
DOI: 10.57745/fmkbax
title: Q265401001_incertitude_datasheet.pdf
DOI: 10.57745/m34ugb
title: Q308040000_incertitude_datasheet.pdf
DOI: 10.57745/mhhrpn
title: Q259331001_incertitude_datasheet.pdf
DOI: 10.57745/sfunmo
title: Q322401001_incertitude_datasheet.pdf
DOI: 10.57745/82kahw
title: Q346401001_incertitude_datasheet.pdf
DOI: 10.57745/a5dscq
title: Q338000200_incertitude_datasheet.pdf
DOI: 10.57745/asthuf
title: Q423101001_incertitude_datasheet.pdf
DOI: 10.57745/njtkuh
title: Q326000100_incertitude_datasheet.pdf
DOI: 10.57745/pgrbrm
title: Q338040000_incertitude_datasheet.pdf
DOI: 10.57745/rttp3l
title: Q414000101_incertitude_datasheet.pdf
DOI: 10.57745/vphn20
title: Q342000000_incertitude_datasheet.pdf
DOI: 10.57745/xqbkm3
title: Q335401001_incertitude_datasheet.pdf
DOI: 10.57745/5vyucw
title: Q484401001_incertitude_datasheet.pdf
DOI: 10.57745/7fmlaw
title: Q456401001_incertitude_datasheet.pdf
DOI: 10.57745/anu6x1
title: Q467000201_incertitude_datasheet.pdf
DOI: 10.57745/bdfpst
title: Q443010000_incertitude_datasheet.pdf
DOI: 10.57745/nkr2zo
title: Q476102001_incertitude_datasheet.pdf
DOI: 10.57745/teykt5
title: Q463401001_incertitude_datasheet.pdf
DOI: 10.57745/twxe1p
title: Q502101001_incertitude_datasheet.pdf
DOI: 10.57745/ussxjn
title: Q440000201_incertitude_datasheet.pdf
DOI: 10.57745/zipcv6
title: Q480101001_incertitude_datasheet.pdf
DOI: 10.57745/zqkpnw
title: Q504101001_incertitude_datasheet.pdf
DOI: 10.57745/2fvaah
title: Q511401001_incertitude_datasheet.pdf
DOI: 10.57745/73zqo8
title: Q614292001_incertitude_datasheet.pdf
DOI: 10.57745/blcitc
title: Q531010000_incertitude_datasheet.pdf
DOI: 10.57745/bskgsv
title: Q515000100_incertitude_datasheet.pdf
DOI: 10.57745/dhex3j
title: Q534000100_incertitude_datasheet.pdf
DOI: 10.57745/fc9260
title: Q610291001_incertitude_datasheet.pdf
DOI: 10.57745/nstboa
title: Q620251001_incertitude_datasheet.pdf
DOI: 10.57745/qxdg8w
title: Q550101001_incertitude_datasheet.pdf
DOI: 10.57745/yfg82b
title: Q560010000_incertitude_datasheet.pdf
DOI: 10.57745/z9sn1r
title: Q632025000_incertitude_datasheet.pdf
DOI: 10.57745/8obtri
title: Q724251001_incertitude_datasheet.pdf
DOI: 10.57745/a9d0ii
title: Q724252001_incertitude_datasheet.pdf
DOI: 10.57745/drg2vk
title: Q700291001_incertitude_datasheet.pdf
DOI: 10.57745/hdgnns
title: Q715000100_incertitude_datasheet.pdf
DOI: 10.57745/k1jp7a
title: Q650025000_incertitude_datasheet.pdf
DOI: 10.57745/khsjy9
title: Q633252101_incertitude_datasheet.pdf
DOI: 10.57745/kusgig
title: Q716015000_incertitude_datasheet.pdf
DOI: 10.57745/pl2dvm
title: Q732252002_incertitude_datasheet.pdf
DOI: 10.57745/qcxzzv
title: Q732025000_incertitude_datasheet.pdf
DOI: 10.57745/8n2pni
title: Q744015000_incertitude_datasheet.pdf
DOI: 10.57745/ashuoe
title: Q735000100_incertitude_datasheet.pdf
DOI: 10.57745/efxxhd
title: Q741291001_incertitude_datasheet.pdf
DOI: 10.57745/n5zrlr
title: Q743000100_incertitude_datasheet.pdf
DOI: 10.57745/ouhb6j
title: Q811000100_incertitude_datasheet.pdf
DOI: 10.57745/qra81j
title: Q800000100_incertitude_datasheet.pdf
DOI: 10.57745/reutc3
title: Q803251001_incertitude_datasheet.pdf
DOI: 10.57745/rmybxx
title: Q742000100_incertitude_datasheet.pdf
DOI: 10.57745/vfahut
title: Q813025000_incertitude_datasheet.pdf
DOI: 10.57745/yetduv
title: Q836000000_incertitude_datasheet.pdf
DOI: 10.57745/6m89ir
title: Q931251001_incertitude_datasheet.pdf
DOI: 10.57745/bkbz0n
title: Q910251001_incertitude_datasheet.pdf
DOI: 10.57745/mr7vir
title: Q903461001_incertitude_datasheet.pdf
DOI: 10.57745/p9vqlf
title: Q916461001_incertitude_datasheet.pdf
DOI: 10.57745/pujpxo
title: Q922025000_incertitude_datasheet.pdf
DOI: 10.57745/uikcqn
title: Q933025000_incertitude_datasheet.pdf
DOI: 10.57745/vuodgc
title: Q935000000_incertitude_datasheet.pdf
DOI: 10.15468/dl.7kgtes
title: Occurrence Download

description: A dataset containing 104 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "TaxonKey is Manis Linnaeus, 1758"
 ]
}

 The dataset includes 104 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026665-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.22672943
title: Simultaneous tolerance intervals for linear regression models using an adjusted product set method

description: Pointwise tolerance intervals for linear regression models are well established in the literature, however, there is no gold standard for a procedure to construct simultaneous tolerance intervals for linear regression models. The existing methods vary considerably with respect to their finite sample performance in terms of coverage probabilities. Moreover, the numerical investigations into their coverage performance have only been conducted under very limited settings. In this work, we investigate the coverage performance for the major procedures available for the construction of simultaneous tolerance intervals for linear regression models, with increasing complexity in the structure of the models considered. We further show that an adjustment made to the confidence level for a product-set-based method provides coverages close to nominal for the majority of models considered, and this adjusted method is nearly always better than each of the other existing methods. Simultaneous tolerance intervals are then constructed and interpreted for a chemical oxygen demand regression model and two models for the strength of polymer-modified cement mortar.
DOI: 10.6084/m9.figshare.22672943.v1
title: Simultaneous tolerance intervals for linear regression models using an adjusted product set method

description: Pointwise tolerance intervals for linear regression models are well established in the literature, however, there is no gold standard for a procedure to construct simultaneous tolerance intervals for linear regression models. The existing methods vary considerably with respect to their finite sample performance in terms of coverage probabilities. Moreover, the numerical investigations into their coverage performance have only been conducted under very limited settings. In this work, we investigate the coverage performance for the major procedures available for the construction of simultaneous tolerance intervals for linear regression models, with increasing complexity in the structure of the models considered. We further show that an adjustment made to the confidence level for a product-set-based method provides coverages close to nominal for the majority of models considered, and this adjusted method is nearly always better than each of the other existing methods. Simultaneous tolerance intervals are then constructed and interpreted for a chemical oxygen demand regression model and two models for the strength of polymer-modified cement mortar.
DOI: 10.6084/m9.figshare.23666331
title: A unified model specification for sparse and dense functional/longitudinal data

description: The semi varying-coefficient additive model is a flexible nonparametric regression method, including varying-coefficient model and additive model as its special cases. However, a complex model may lead over-fitting phenomenon, which motivates us to develop a set of testing procedure to judge whether a parsimonious submodel is sufficient or not. Specifically, we propose hypothesis testings to check time-varying property of varying-coefficient component functions and linearity of additive component functions, respectively. For repeated measurements data, it is a subjective choice between sparse and dense case, which may lead to wrong statistical inference. One major contribution of this paper is to introduce consistent testing methodologies in a unified framework of sparse, dense and ultra dense cases of the data, which avoids a subjective choice of data types in practical applications. Extensive Monte Carlo simulation studies investigating the finite sample performance of the proposed methodologies confirm our asymptotic results. We further illustrate our methodologies <i>via</i> two real-life data applications.
DOI: 10.6084/m9.figshare.23666331.v1
title: A unified model specification for sparse and dense functional/longitudinal data

description: The semi varying-coefficient additive model is a flexible nonparametric regression method, including varying-coefficient model and additive model as its special cases. However, a complex model may lead over-fitting phenomenon, which motivates us to develop a set of testing procedure to judge whether a parsimonious submodel is sufficient or not. Specifically, we propose hypothesis testings to check time-varying property of varying-coefficient component functions and linearity of additive component functions, respectively. For repeated measurements data, it is a subjective choice between sparse and dense case, which may lead to wrong statistical inference. One major contribution of this paper is to introduce consistent testing methodologies in a unified framework of sparse, dense and ultra dense cases of the data, which avoids a subjective choice of data types in practical applications. Extensive Monte Carlo simulation studies investigating the finite sample performance of the proposed methodologies confirm our asymptotic results. We further illustrate our methodologies <i>via</i> two real-life data applications.
DOI: 10.6084/m9.figshare.22551401
title: Simulation studies on the estimation of sensitivity and specificity in the absence of a gold standard and with rare positive frequencies

description: In the absence of a gold standard, sensitivity and specificity could be evaluated using the Bayesian latent class model underlying true positives and true negatives. However, when the frequency of positivity is limited owing to low prevalence, the estimates may be strongly influenced by prior information or small-sample bias. In this study, we evaluated the performance of the Bayesian latent class model with two independent tests under a rare frequency of positivity, varying the strength and way of giving prior information under the conditional independence assumption is satisfied. Throughout the simulation experiments, a small-sample bias led to underestimation and overestimation when the frequency of positivity was low. Furthermore, we observed that placing an informative prior distribution for only one of the two tests resulted in a constant bias of sensitivity or specificity for the other test, regardless of the strength of the prior information.
DOI: 10.15468/dl.m3tsej
title: Occurrence Download

description: A dataset containing 3817 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ramphocelus melanogaster (Swainson, 1838)"
 ]
}

 The dataset includes 3817 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026666-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.22551401.v1
title: Simulation studies on the estimation of sensitivity and specificity in the absence of a gold standard and with rare positive frequencies

description: In the absence of a gold standard, sensitivity and specificity could be evaluated using the Bayesian latent class model underlying true positives and true negatives. However, when the frequency of positivity is limited owing to low prevalence, the estimates may be strongly influenced by prior information or small-sample bias. In this study, we evaluated the performance of the Bayesian latent class model with two independent tests under a rare frequency of positivity, varying the strength and way of giving prior information under the conditional independence assumption is satisfied. Throughout the simulation experiments, a small-sample bias led to underestimation and overestimation when the frequency of positivity was low. Furthermore, we observed that placing an informative prior distribution for only one of the two tests resulted in a constant bias of sensitivity or specificity for the other test, regardless of the strength of the prior information.
DOI: 10.15468/dl.xrpgtr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sebastodes owstoni Jordan & Thompson, 1914",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026667-241126133413365/datasets/export for details.
DOI: 10.57745/asml8h
title: Explore2_Notice_fiche_incertitude_VF.pdf
DOI: 10.57745/isyi6r
title: L001061101_incertitude_datasheet.pdf
DOI: 10.57745/vdjbko
title: L005063001_incertitude_datasheet.pdf
DOI: 10.57745/5gx3kr
title: L020151001_incertitude_datasheet.pdf
DOI: 10.57745/9urb51
title: L023151001_incertitude_datasheet.pdf
DOI: 10.57745/a8tvi5
title: L014061001_incertitude_datasheet.pdf
DOI: 10.57745/cagdsg
title: L009302002_incertitude_datasheet.pdf
DOI: 10.57745/oxfcjv
title: L031401001_incertitude_datasheet.pdf
DOI: 10.57745/pfwhfz
title: L011030000_incertitude_datasheet.pdf
DOI: 10.57745/siibe1
title: L030015000_incertitude_datasheet.pdf
DOI: 10.57745/tmjpqw
title: L009302001_incertitude_datasheet.pdf
DOI: 10.57745/v8tuxb
title: L012303001_incertitude_datasheet.pdf
DOI: 10.57745/x5rfke
title: L012302001_incertitude_datasheet.pdf
DOI: 10.57745/xk908n
title: L030000101_incertitude_datasheet.pdf
DOI: 10.57745/6uhxqt
title: L070061001_incertitude_datasheet.pdf
DOI: 10.57745/8uqqei
title: L080030000_incertitude_datasheet.pdf
DOI: 10.57745/bd5d9p
title: L056301001_incertitude_datasheet.pdf
DOI: 10.57745/etnwdx
title: L062401001_incertitude_datasheet.pdf
DOI: 10.57745/gfte67
title: L062061001_incertitude_datasheet.pdf
DOI: 10.57745/llx4vd
title: L061402001_incertitude_datasheet.pdf
DOI: 10.57745/ocmtj2
title: L040061001_incertitude_datasheet.pdf
DOI: 10.57745/qkjali
title: L081301001_incertitude_datasheet.pdf
DOI: 10.57745/x8btzq
title: L061400000_incertitude_datasheet.pdf
DOI: 10.57745/y5h5l7
title: L032151001_incertitude_datasheet.pdf
DOI: 10.57745/zgxhec
title: L051301001_incertitude_datasheet.pdf
DOI: 10.57745/4q9hhg
title: L092061002_incertitude_datasheet.pdf
DOI: 10.57745/5kgz5b
title: L091402001_incertitude_datasheet.pdf
DOI: 10.57745/62rhco
title: L094061001_incertitude_datasheet.pdf
DOI: 10.57745/7nzjth
title: L111301001_incertitude_datasheet.pdf
DOI: 10.57745/hnfnju
title: L100401001_incertitude_datasheet.pdf
DOI: 10.57745/itifrz
title: L111302001_incertitude_datasheet.pdf
DOI: 10.57745/odqrym
title: L093000100_incertitude_datasheet.pdf
DOI: 10.57745/yhp9z5
title: L111302100_incertitude_datasheet.pdf
DOI: 10.57745/0z0q6a
title: L131000400_incertitude_datasheet.pdf
DOI: 10.57745/a2zsn8
title: L143000200_incertitude_datasheet.pdf
DOI: 10.57745/epivku
title: L202000300_incertitude_datasheet.pdf
DOI: 10.57745/h5k8lv
title: L120000301_incertitude_datasheet.pdf
DOI: 10.57745/hrguwb
title: L144061001_incertitude_datasheet.pdf
DOI: 10.57745/o95ldp
title: L131000101_incertitude_datasheet.pdf
DOI: 10.57745/oqcz8e
title: L132400000_incertitude_datasheet.pdf
DOI: 10.57745/upjeqs
title: L130000200_incertitude_datasheet.pdf
DOI: 10.57745/x0t0xa
title: L140061001_incertitude_datasheet.pdf
DOI: 10.57745/ylgjdm
title: L200000300_incertitude_datasheet.pdf
DOI: 10.57745/35payh
title: L221301001_incertitude_datasheet.pdf
DOI: 10.57745/gef7sl
title: L211401300_incertitude_datasheet.pdf
DOI: 10.57745/ka6nea
title: L210301300_incertitude_datasheet.pdf
DOI: 10.57745/ku9sxo
title: L220161002_incertitude_datasheet.pdf
DOI: 10.57745/qgnsot
title: L203000200_incertitude_datasheet.pdf
DOI: 10.57745/rx4uqi
title: L210300501_incertitude_datasheet.pdf
DOI: 10.57745/snvjpq
title: L210301001_incertitude_datasheet.pdf
DOI: 10.57745/vx7kmg
title: L225030000_incertitude_datasheet.pdf
DOI: 10.57745/xd2bzv
title: L211401001_incertitude_datasheet.pdf
DOI: 10.57745/7nbjiy
title: L231301401_incertitude_datasheet.pdf
DOI: 10.57745/ctnfaj
title: L234161003_incertitude_datasheet.pdf
DOI: 10.57745/hduwvv
title: L231301001_incertitude_datasheet.pdf
DOI: 10.57745/i2ztnu
title: L240402001_incertitude_datasheet.pdf
DOI: 10.57745/n38fkx
title: L234161001_incertitude_datasheet.pdf
DOI: 10.57745/p7pdmr
title: L225301001_incertitude_datasheet.pdf
DOI: 10.57745/srehgw
title: L231301101_incertitude_datasheet.pdf
DOI: 10.57745/vlulog
title: L233401001_incertitude_datasheet.pdf
DOI: 10.57745/y0wqsp
title: L240401001_incertitude_datasheet.pdf
DOI: 10.57745/zfawbp
title: L232440000_incertitude_datasheet.pdf
DOI: 10.57745/zjuj8w
title: L233401200_incertitude_datasheet.pdf
DOI: 10.57745/1lindt
title: L244030000_incertitude_datasheet.pdf
DOI: 10.57745/2ienzo
title: L250161001_incertitude_datasheet.pdf
DOI: 10.57745/5zg135
title: L253016100_incertitude_datasheet.pdf
DOI: 10.57745/bm66al
title: L244301001_incertitude_datasheet.pdf
DOI: 10.57745/db1794
title: L252301001_incertitude_datasheet.pdf
DOI: 10.57745/devbxy
title: L251000300_incertitude_datasheet.pdf
DOI: 10.57745/idwzx1
title: L252301100_incertitude_datasheet.pdf
DOI: 10.57745/nxu8yi
title: L242401400_incertitude_datasheet.pdf
DOI: 10.57745/sknaqc
title: L243000300_incertitude_datasheet.pdf
DOI: 10.57745/y0cuuk
title: L240404001_incertitude_datasheet.pdf
DOI: 10.57745/zdkq2i
title: L240403001_incertitude_datasheet.pdf
DOI: 10.57745/4cllip
title: L312301001_incertitude_datasheet.pdf
DOI: 10.57745/6qeobn
title: L302000300_incertitude_datasheet.pdf
DOI: 10.57745/co0cjq
title: L323006000_incertitude_datasheet.pdf
DOI: 10.57745/fdhd6a
title: L311000100_incertitude_datasheet.pdf
DOI: 10.57745/kr29jv
title: L312301100_incertitude_datasheet.pdf
DOI: 10.57745/mg42qa
title: L403301001_incertitude_datasheet.pdf
DOI: 10.57745/oarxei
title: L301000100_incertitude_datasheet.pdf
DOI: 10.57745/uurezk
title: L303301001_incertitude_datasheet.pdf
DOI: 10.57745/xd7wlj
title: L401071001_incertitude_datasheet.pdf
DOI: 10.57745/xwakfr
title: L320062001_incertitude_datasheet.pdf
DOI: 10.57745/2vubpe
title: L421071001_incertitude_datasheet.pdf
DOI: 10.57745/aw2xrc
title: L431400000_incertitude_datasheet.pdf
DOI: 10.57745/fezsee
title: L422071001_incertitude_datasheet.pdf
DOI: 10.57745/ljpsdt
title: L452302001_incertitude_datasheet.pdf
DOI: 10.57745/nkpff3
title: L440000101_incertitude_datasheet.pdf
DOI: 10.57745/oosf37
title: L430017000_incertitude_datasheet.pdf
DOI: 10.57745/urgz27
title: L420000301_incertitude_datasheet.pdf
DOI: 10.57745/vxjmi0
title: L452302002_incertitude_datasheet.pdf
DOI: 10.57745/wuq13s
title: L410071001_incertitude_datasheet.pdf
DOI: 10.57745/zslozj
title: L441171001_incertitude_datasheet.pdf
DOI: 10.57745/4nsl4n
title: L453000201_incertitude_datasheet.pdf
DOI: 10.57745/a7qs2f
title: L454071001_incertitude_datasheet.pdf
DOI: 10.57745/hlpgn6
title: L503401001_incertitude_datasheet.pdf
DOI: 10.57745/iyemdl
title: L473071001_incertitude_datasheet.pdf
DOI: 10.57745/jxuqt2
title: L454072001_incertitude_datasheet.pdf
DOI: 10.57745/kcljqy
title: L502181001_incertitude_datasheet.pdf
DOI: 10.57745/ntket8
title: L470071001_incertitude_datasheet.pdf
DOI: 10.57745/orxcd1
title: L465301001_incertitude_datasheet.pdf
DOI: 10.57745/pg3j1a
title: L501018000_incertitude_datasheet.pdf
DOI: 10.57745/xfj9sf
title: L500181001_incertitude_datasheet.pdf
DOI: 10.57745/xrxg2b
title: L471071001_incertitude_datasheet.pdf
DOI: 10.57745/2ejc31
title: L510018000_incertitude_datasheet.pdf
DOI: 10.57745/bdzvx9
title: L530181001_incertitude_datasheet.pdf
DOI: 10.57745/hcqng7
title: L532301001_incertitude_datasheet.pdf
DOI: 10.57745/kfjj2f
title: L522302001_incertitude_datasheet.pdf
DOI: 10.57745/kjv40s
title: L540181001_incertitude_datasheet.pdf
DOI: 10.57745/konfnb
title: L510181001_incertitude_datasheet.pdf
DOI: 10.57745/usbpun
title: L541018000_incertitude_datasheet.pdf
DOI: 10.57745/w8a72g
title: L503401200_incertitude_datasheet.pdf
DOI: 10.57745/zm8apt
title: L513401001_incertitude_datasheet.pdf
DOI: 10.57745/4hxrd2
title: L541182301_incertitude_datasheet.pdf
DOI: 10.57745/na5cxi
title: L541181001_incertitude_datasheet.pdf
DOI: 10.57745/pn1hsy
title: L556000102_incertitude_datasheet.pdf
DOI: 10.57745/rzpgqq
title: L560000100_incertitude_datasheet.pdf
DOI: 10.57745/ueoqwu
title: L561000100_incertitude_datasheet.pdf
DOI: 10.57745/vdslgv
title: L551191001_incertitude_datasheet.pdf
DOI: 10.57745/zmbj1w
title: L562301001_incertitude_datasheet.pdf
DOI: 10.57745/2k9p0d
title: L563030000_incertitude_datasheet.pdf
DOI: 10.57745/7zspzr
title: L565031000_incertitude_datasheet.pdf
DOI: 10.57745/bxlid2
title: L571000100_incertitude_datasheet.pdf
DOI: 10.57745/euvgsj
title: L567000100_incertitude_datasheet.pdf
DOI: 10.57745/owzzm6
title: L567000301_incertitude_datasheet.pdf
DOI: 10.57745/ribpba
title: L564000100_incertitude_datasheet.pdf
DOI: 10.57745/xwppeq
title: L565000100_incertitude_datasheet.pdf
DOI: 10.57745/5k2t97
title: L574192002_incertitude_datasheet.pdf
DOI: 10.57745/bis7uf
title: L574191001_incertitude_datasheet.pdf
DOI: 10.57745/h1k7he
title: L600071001_incertitude_datasheet.pdf
DOI: 10.57745/iowcwf
title: L610000100_incertitude_datasheet.pdf
DOI: 10.57745/myzndb
title: L602071001_incertitude_datasheet.pdf
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