{
  "_id": "6a0f7187acfb0bcc41c5f7db",
  "Package": "RDS",
  "Type": "Package",
  "Title": "Respondent-Driven Sampling",
  "Version": "0.9-10",
  "Date": "2024-09-05",
  "Authors@R": "c(person(\"Mark S.\", \"Handcock\", role=c(\"aut\",\"cre\"), email=\"handcock@stat.ucla.edu\", comment=c(ORCID=\"0000-0002-9985-2785\")),\nperson(\"Krista J.\", \"Gile\", role=c(\"aut\"), email=\"gile@math.umass.edu\"),\nperson(\"Ian E.\", \"Fellows\", role=c(\"aut\"), email=\"ian@fellstat.com\"),\nperson(\"W. Whipple\", \"Neely\", role=c(\"ctb\"), email=\"wwneely@stat.washington.edu\"))",
  "Maintainer": "Mark S. Handcock <handcock@stat.ucla.edu>",
  "Description": "Provides functionality for carrying out estimation with\ndata collected using Respondent-Driven Sampling. This includes\nHeckathorn's RDS-I and RDS-II estimators as well as Gile's\nSequential Sampling estimator. The package is part of the \"RDS\nAnalyst\" suite of packages for the analysis of\nrespondent-driven sampling data. See Gile and Handcock (2010)\n<doi:10.1111/j.1467-9531.2010.01223.x>, Gile and Handcock\n(2015) <doi:10.1111/rssa.12091> and Gile, Beaudry, Handcock and\nOtt (2018) <doi:10.1146/annurev-statistics-031017-100704>.",
  "License": "LGPL-2.1",
  "URL": "https://hpmrg.org",
  "Encoding": "UTF-8",
  "RoxygenNote": "7.3.2",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-05-21 07:12:39 UTC",
    "User": "root"
  },
  "Author": "Mark S. Handcock [aut, cre]\n(<https://orcid.org/0000-0002-9985-2785>), Krista J. Gile\n[aut], Ian E. Fellows [aut], W. Whipple Neely [ctb]",
  "Config/pak/sysreqs": "cmake libglpk-dev make libicu-dev libuv1-dev\nlibxml2-dev",
  "Repository": "https://handcock.r-universe.dev",
  "Date/Publication": "2024-09-07 02:50:27 UTC",
  "RemoteUrl": "https://github.com/cran/RDS",
  "RemoteRef": "HEAD",
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  "_user": "handcock",
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  "_created": "2026-05-21T07:12:39.000Z",
  "_published": "2026-05-21T20:56:39.601Z",
  "_distro": "noble",
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    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 0.9-10\n",
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    "name": "Mark S. Handcock",
    "email": "handcock@stat.ucla.edu",
    "login": "handcock",
    "description": "Distinguished Professor of Statistics, UCLA",
    "uuid": 2207202,
    "orcid": "0000-0002-9985-2785"
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      "version": ">= 2.5.1",
      "role": "Depends"
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      "role": "Depends"
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    {
      "package": "gridExtra",
      "role": "Imports"
    },
    {
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      "version": ">= 2.0.0",
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      "package": "network",
      "role": "Imports"
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    {
      "package": "igraph",
      "role": "Imports"
    },
    {
      "package": "reshape2",
      "role": "Imports"
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    {
      "package": "scales",
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    {
      "package": "anytime",
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      "package": "Hmisc",
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    },
    {
      "package": "statnet.common",
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      "role": "Suggests"
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      "role": "Suggests"
    },
    {
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      "role": "Suggests"
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  "_selfowned": true,
  "_usedby": 3,
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  "_stars": 1,
  "_contributors": [
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    "type": "user",
    "name": "Mark S. Handcock",
    "description": "Distinguished Professor of Statistics, UCLA"
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/RDS"
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  "_mentions": 18,
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  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/RDS.html",
    "manual.pdf"
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  "_realowner": "handcock",
  "_cranurl": false,
  "_releases": [
    {
      "version": "0.01",
      "date": "2009-04-22"
    },
    {
      "version": "0.5",
      "date": "2013-11-28"
    },
    {
      "version": "0.6",
      "date": "2014-05-07"
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    {
      "version": "0.7",
      "date": "2015-01-20"
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    {
      "version": "0.7-1",
      "date": "2015-03-24"
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      "date": "2015-05-12"
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    {
      "version": "0.7-4",
      "date": "2015-12-29"
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      "version": "0.7-5",
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      "date": "2016-03-26"
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      "date": "2016-12-27"
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      "date": "2017-09-16"
    },
    {
      "version": "0.8-1",
      "date": "2017-12-01"
    },
    {
      "version": "0.9-0",
      "date": "2019-05-31"
    },
    {
      "version": "0.9-2",
      "date": "2019-12-14"
    },
    {
      "version": "0.9-3",
      "date": "2021-03-29"
    },
    {
      "version": "0.9-5",
      "date": "2023-01-14"
    },
    {
      "version": "0.9-6",
      "date": "2023-02-10"
    },
    {
      "version": "0.9-7",
      "date": "2023-08-20"
    },
    {
      "version": "0.9-9",
      "date": "2024-02-01"
    },
    {
      "version": "0.9-10",
      "date": "2024-09-06"
    }
  ],
  "_exports": [
    "as.char",
    "as.rds.data.frame",
    "assert.valid.rds.data.frame",
    "bootstrap.contingency.test",
    "bootstrap.incidence",
    "bottleneck.plot",
    "compute.weights",
    "control.rds.estimates",
    "convergence.plot",
    "count.transitions",
    "cumulative.estimate",
    "differential.activity.estimates",
    "export.rds.interval.estimate",
    "get.h.hat",
    "get.id",
    "get.net.size",
    "get.number.of.recruits",
    "get.population.size",
    "get.recruitment.time",
    "get.rid",
    "get.seed.id",
    "get.seed.rid",
    "get.stationary.distribution",
    "get.wave",
    "gile.ss.weights",
    "has.recruitment.time",
    "hcg.replicate.weights",
    "hcg.weights",
    "homophily.estimates",
    "impute.degree",
    "impute.visibility",
    "impute.visibility_mle",
    "is.rds.data.frame",
    "is.rds.interval.estimate",
    "is.rds.interval.estimate.list",
    "LRT.trend",
    "LRT.trend.test",
    "LRT.value.trend",
    "MA.estimates",
    "RDS.bootstrap.intervals",
    "RDS.compare.proportions",
    "RDS.compare.two.proportions",
    "RDS.HCG.estimates",
    "RDS.I.estimates",
    "rds.I.weights",
    "RDS.II.estimates",
    "rds.interval.estimate",
    "RDS.SS.estimates",
    "rdssampleC",
    "read.rdsat",
    "read.rdsobj",
    "reingold.tilford.plot",
    "rid.from.coupons",
    "set.control.class",
    "show.rds.data.frame",
    "ult",
    "vh.weights",
    "write.graphviz",
    "write.netdraw",
    "write.rdsat",
    "write.rdsobj"
  ],
  "_datasets": [
    {
      "name": "faux",
      "title": "A Simulated RDS Data Set",
      "object": "faux",
      "file": "faux.RData",
      "class": [
        "rds.data.frame",
        "data.frame"
      ],
      "fields": [
        "id",
        "recruiter.id",
        "X",
        "Y",
        "Z",
        "network.size",
        "wave",
        "seed",
        "weights"
      ],
      "rows": 389,
      "table": true,
      "tojson": true
    },
    {
      "name": "fauxmadrona",
      "title": "A Simulated RDS Data Set with no seed dependency",
      "object": "fauxmadrona",
      "file": "fauxmadrona.RData",
      "class": [
        "rds.data.frame",
        "data.frame"
      ],
      "fields": [
        "id",
        "recruiter.id",
        "degree",
        "disease",
        "todiseased",
        "tonondiseased",
        "wave",
        "seed",
        "weights"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
    {
      "name": "fauxmadrona.network",
      "title": "A Simulated RDS Data Set with no seed dependency",
      "object": "fauxmadrona",
      "file": "fauxmadrona.RData",
      "class": [
        "network"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "fauxsycamore",
      "title": "A Simulated RDS Data Set with extreme seed dependency",
      "object": "fauxsycamore",
      "file": "fauxsycamore.RData",
      "class": [
        "rds.data.frame",
        "data.frame"
      ],
      "fields": [
        "id",
        "recruiter.id",
        "degree",
        "disease",
        "tonondiseased",
        "todiseased",
        "wave",
        "seed",
        "weights"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
    {
      "name": "fauxsycamore.network",
      "title": "A Simulated RDS Data Set with extreme seed dependency",
      "object": "fauxsycamore",
      "file": "fauxsycamore.RData",
      "class": [
        "network"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "fauxtime",
      "title": "A Simulated RDS Data Set",
      "object": "fauxtime",
      "file": "fauxtime.RData",
      "class": [
        "rds.data.frame",
        "data.frame"
      ],
      "fields": [
        "SER",
        "NETWORK",
        "DATEINTERVIEW",
        "var1",
        "recruiter.id"
      ],
      "rows": 511,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "indexing-methods",
      "title": "indexing",
      "topics": [
        "[,rds.data.frame-method",
        "[.rds.data.frame"
      ]
    },
    {
      "page": "extract-methods",
      "title": "indexing",
      "topics": [
        "[<-,rds.data.frame-method",
        "[<-.rds.data.frame"
      ]
    },
    {
      "page": "as.char",
      "title": "converts to character with minimal loss of precision for numeric variables",
      "topics": [
        "as.char"
      ]
    },
    {
      "page": "as.rds.data.frame",
      "title": "Coerces a data.frame object into an rds.data.frame object.",
      "topics": [
        "as.rds.data.frame"
      ]
    },
    {
      "page": "assert.valid.rds.data.frame",
      "title": "Does various checks and throws errors if x is not a valid rds.data.frame",
      "topics": [
        "assert.valid.rds.data.frame"
      ]
    },
    {
      "page": "bootstrap.contingency.test",
      "title": "Performs a bootstrap test of independance between two categorical variables",
      "topics": [
        "bootstrap.contingency.test"
      ]
    },
    {
      "page": "bootstrap.incidence",
      "title": "Calculates incidence and bootstrap confidence intervals for immunoassay data collected with RDS",
      "topics": [
        "bootstrap.incidence"
      ]
    },
    {
      "page": "bottleneck.plot",
      "title": "Bottleneck Plot",
      "topics": [
        "bottleneck.plot"
      ]
    },
    {
      "page": "compute.weights",
      "title": "Compute estimates of the sampling weights of the respondent's observations based on various estimators",
      "topics": [
        "compute.weights"
      ]
    },
    {
      "page": "control.list.accessor",
      "title": "Named element accessor for ergm control lists",
      "topics": [
        "$.control.list",
        "control.list.accessor"
      ]
    },
    {
      "page": "control.rds.estimates",
      "title": "Auxiliary for Controlling RDS.bootstrap.intervals",
      "topics": [
        "control.rds.estimates"
      ]
    },
    {
      "page": "convergence.plot",
      "title": "Convergence Plots",
      "topics": [
        "convergence.plot"
      ]
    },
    {
      "page": "count.transitions",
      "title": "Counts the number or recruiter->recruitee transitions between different levels of the grouping variable.",
      "topics": [
        "count.transitions"
      ]
    },
    {
      "page": "cumulative.estimate",
      "title": "Calculates estimates at each successive wave of the sampling process",
      "topics": [
        "cumulative.estimate"
      ]
    },
    {
      "page": "differential.activity.estimates",
      "title": "Differential Activity between groups",
      "topics": [
        "differential.activity.estimates"
      ]
    },
    {
      "page": "export.rds.interval.estimate",
      "title": "Convert the output of print.rds.interval.estimate from a character data.frame to a numeric matrix",
      "topics": [
        "export.rds.interval.estimate"
      ]
    },
    {
      "page": "faux",
      "title": "A Simulated RDS Data Set",
      "topics": [
        "faux"
      ]
    },
    {
      "page": "fauxmadrona",
      "title": "A Simulated RDS Data Set with no seed dependency",
      "topics": [
        "fauxmadrona",
        "fauxmadrona.network"
      ]
    },
    {
      "page": "fauxsycamore",
      "title": "A Simulated RDS Data Set with extreme seed dependency",
      "topics": [
        "fauxsycamore",
        "fauxsycamore.network"
      ]
    },
    {
      "page": "fauxtime",
      "title": "A Simulated RDS Data Set",
      "topics": [
        "fauxtime"
      ]
    },
    {
      "page": "get.h.hat",
      "title": "Get Horvitz-Thompson estimator assuming inclusion probability proportional to the inverse of network.var (i.e. degree).",
      "topics": [
        "get.h.hat"
      ]
    },
    {
      "page": "get.id",
      "title": "Get the subject id",
      "topics": [
        "get.id"
      ]
    },
    {
      "page": "get.net.size",
      "title": "Returns the network size of each subject (i.e. their degree).",
      "topics": [
        "get.net.size"
      ]
    },
    {
      "page": "get.number.of.recruits",
      "title": "Calculates the number of (direct) recuits for each respondent.",
      "topics": [
        "get.number.of.recruits"
      ]
    },
    {
      "page": "get.population.size",
      "title": "Returns the population size associated with the data.",
      "topics": [
        "get.population.size"
      ]
    },
    {
      "page": "get.recruitment.time",
      "title": "Returns the recruitment time for each subject",
      "topics": [
        "get.recruitment.time"
      ]
    },
    {
      "page": "get.rid",
      "title": "Get recruiter id",
      "topics": [
        "get.rid"
      ]
    },
    {
      "page": "get.seed.id",
      "title": "Calculates the root seed id for each node of the recruitement tree.",
      "topics": [
        "get.seed.id"
      ]
    },
    {
      "page": "get.seed.rid",
      "title": "Gets the recruiter id associated with the seeds",
      "topics": [
        "get.seed.rid"
      ]
    },
    {
      "page": "get.stationary.distribution",
      "title": "Markov chain statistionary distribution",
      "topics": [
        "get.stationary.distribution"
      ]
    },
    {
      "page": "get.wave",
      "title": "Calculates the depth of the recruitment tree (i.e. the recruitment wave) at each node.",
      "topics": [
        "get.wave"
      ]
    },
    {
      "page": "gile.ss.weights",
      "title": "Weights using Giles SS estimator",
      "topics": [
        "gile.ss.weights"
      ]
    },
    {
      "page": "has.recruitment.time",
      "title": "RDS data.frame has recruitment time information",
      "topics": [
        "has.recruitment.time"
      ]
    },
    {
      "page": "hcg.replicate.weights",
      "title": "HCG parametric bootstrap replicate weights",
      "topics": [
        "hcg.replicate.weights"
      ]
    },
    {
      "page": "hcg.weights",
      "title": "homophily configuration graph weights",
      "topics": [
        "hcg.weights"
      ]
    },
    {
      "page": "homophily.estimates",
      "title": "This function computes an estimate of the population homophily and the recruitment homophily based on a categorical variable.",
      "topics": [
        "homophily.estimates"
      ]
    },
    {
      "page": "impute.degree",
      "title": "Imputes missing degree values",
      "topics": [
        "impute.degree"
      ]
    },
    {
      "page": "impute.visibility",
      "title": "Estimates each person's personal visibility based on their self-reported degree and the number of their (direct) recruits. It uses the time the person was recruited as a factor in determining the number of recruits they produce.",
      "topics": [
        "impute.visibility"
      ]
    },
    {
      "page": "impute.visibility_mle",
      "title": "Estimates each person's personal visibility based on their self-reported degree and the number of their (direct) recruits. It uses the time the person was recruited as a factor in determining the number of recruits they produce.",
      "topics": [
        "impute.visibility_mle"
      ]
    },
    {
      "page": "is.rds.data.frame",
      "title": "Is an instance of rds.data.frame",
      "topics": [
        "is.rds.data.frame"
      ]
    },
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      "page": "is.rds.interval.estimate",
      "title": "Is an instance of rds.interval.estimate",
      "topics": [
        "is.rds.interval.estimate"
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    },
    {
      "page": "is.rds.interval.estimate.list",
      "title": "Is an instance of rds.interval.estimate.list This is a (typically time ordered) sequence of RDS estimates of a comparable quantity",
      "topics": [
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    },
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      "page": "LRT.trend.test",
      "title": "Compute a test of trend in prevalences based on a likelihood-ratio statistic",
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    },
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    {
      "page": "MA.estimates",
      "title": "MA Estimates",
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    },
    {
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      "title": "Diagnostic plots for the RDS recruitment process",
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      "page": "print.differential.activity.estimate",
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      "page": "print.rds.data.frame",
      "title": "Displays an rds.data.frame",
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      "page": "print.rds.interval.estimate",
      "title": "Prints an 'rds.interval.estimate' object",
      "topics": [
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    },
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      "page": "print.summary.svyglm.RDS",
      "title": "Summarizing Generalized Linear Model Fits with Odds Ratios",
      "topics": [
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    },
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      "page": "RDS.I.estimates",
      "title": "Compute RDS-I Estimates",
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    },
    {
      "page": "rds.I.weights",
      "title": "RDS-I weights",
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    {
      "page": "RDS.II.estimates",
      "title": "RDS-II Estimates",
      "topics": [
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    },
    {
      "page": "rds.interval.estimate",
      "title": "An object of class rds.interval.estimate",
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    },
    {
      "page": "RDS.SS.estimates",
      "title": "Gile's SS Estimates",
      "topics": [
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    },
    {
      "page": "rdssampleC",
      "title": "Create RDS samples with given characteristics",
      "topics": [
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    },
    {
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      "title": "Import data from the 'RDSAT' format as an 'rds.data.frame'",
      "topics": [
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    {
      "page": "read.rdsobj",
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      "page": "reingold.tilford.plot",
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      "page": "rid.from.coupons",
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      "topics": [
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    {
      "page": "set.control.class",
      "title": "Set the class of the control list",
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      "page": "show.rds.data.frame",
      "title": "Displays an rds.data.frame",
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    {
      "page": "summary.svyglm.RDS",
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      "topics": [
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      "page": "ult",
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