diff --git a/Project.toml b/Project.toml
index df5459c..02d7a7d 100644
--- a/Project.toml
+++ b/Project.toml
@@ -16,15 +16,12 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 EffectSizes = "e248de7e-9197-5860-972e-353a2af44d75"
 ElasticArrays = "fdbdab4c-e67f-52f5-8c3f-e7b388dad3d4"
-FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 FittedItemBanks = "3f797b09-34e4-41d7-acf6-3302ae3248a5"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 HypothesisTests = "09f84164-cd44-5f33-b23f-e6b0d136a0d5"
-Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 Lazy = "50d2b5c4-7a5e-59d5-8109-a42b560f39c0"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogarithmicNumbers = "aa2f6b4e-9042-5d33-9679-40d3a6b85899"
-MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 Mmap = "a63ad114-7e13-5084-954f-fe012c677804"
 PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
 PrettyPrinting = "54e16d92-306c-5ea0-a30b-337be88ac337"
@@ -33,8 +30,6 @@ PsychometricsBazaarBase = "b0d9cada-d963-45e9-a4c6-4746243987f1"
 QuickHeaps = "30b38841-0f52-47f8-a5f8-18d5d4064379"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
-Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
-SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
@@ -55,15 +50,12 @@ Distributions = "^0.25.88"
 DocStringExtensions = " ^0.9"
 EffectSizes = "^1.0.1"
 ElasticArrays = "1.2.12"
-FillArrays = "0.13, 1.5.0"
 FittedItemBanks = "^0.7.3"
 ForwardDiff = "1"
 HypothesisTests = "^0.10.12, ^0.11.0"
-Interpolations = "^0.14, ^0.15"
 Lazy = "0.15"
 LinearAlgebra = "^1.11"
 LogarithmicNumbers = "1"
-MacroTools = "^0.5.6"
 Mmap = "^1.11"
 PrecompileTools = "1.2.1"
 PrettyPrinting = "0.4.2"
@@ -72,8 +64,6 @@ PsychometricsBazaarBase = "^0.8.7"
 QuickHeaps = "0.2.2"
 Random = "^1.11"
 Reexport = "1"
-Setfield = "^1"
-SparseArrays = "^1.11"
 StaticArrays = "1"
 StatsBase = "^0.34"
 StatsFuns = "^0.9.15, ^1"
diff --git a/profile/Project.toml b/profile/Project.toml
deleted file mode 100644
index c984419..0000000
--- a/profile/Project.toml
+++ /dev/null
@@ -1,6 +0,0 @@
-[deps]
-ComputerAdaptiveTesting = "5a0d4f34-1f62-4a66-80fe-87aba0485488"
-PProf = "e4faabce-9ead-11e9-39d9-4379958e3056"
-StatProfilerHTML = "a8a75453-ed82-57c9-9e16-4cd1196ecbf5"
-BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
-Coverage = "a2441757-f6aa-5fb2-8edb-039e3f45d037"
diff --git a/profile/clear_mems.sh b/profile/clear_mems.sh
deleted file mode 100755
index 08986b2..0000000
--- a/profile/clear_mems.sh
+++ /dev/null
@@ -1,4 +0,0 @@
-#!/bin/bash
-
-PATTERN="*.$1.mem"
-find -name $PATTERN -exec rm -i {} \;
\ No newline at end of file
diff --git a/profile/does_quadgk_alloc.jl b/profile/does_quadgk_alloc.jl
deleted file mode 100644
index ea74839..0000000
--- a/profile/does_quadgk_alloc.jl
+++ /dev/null
@@ -1,10 +0,0 @@
-using QuadGK
-using Distributions
-using Profile
-
-const int_tol = 1e-6
-const std_norm = Normal()
-norm_cdf = x -> cdf(std_norm, x)
-quadgk(norm_cdf, -10.0, 1.0, int_tol)[1]
-Profile.clear_malloc_data()
-quadgk(norm_cdf, -10.0, 1.0, int_tol)[1]
diff --git a/profile/mv_mems.sh b/profile/mv_mems.sh
deleted file mode 100755
index ee18c5a..0000000
--- a/profile/mv_mems.sh
+++ /dev/null
@@ -1,5 +0,0 @@
-#!/bin/bash
-
-mkdir -p $2
-PATTERN="*.$1.mem"
-find -name $PATTERN -exec mv {} $2/ \;
\ No newline at end of file
diff --git a/profile/next_items.jl b/profile/next_items.jl
deleted file mode 100644
index ef8b5fc..0000000
--- a/profile/next_items.jl
+++ /dev/null
@@ -1,204 +0,0 @@
-using ComputerAdaptiveTesting.DummyData: dummy_3pl,
-    dummy_mirt_4pl, std_normal, std_mv_normal
-using ComputerAdaptiveTesting.Responses
-using ComputerAdaptiveTesting.Aggregators
-using ComputerAdaptiveTesting.Integrators
-using ComputerAdaptiveTesting.NextItemRules
-import Profile
-import PProf
-using Distributions: Normal
-using ArgParse
-using StatProfilerHTML
-using StatsBase: sample
-using BenchmarkTools
-
-function get_ability_estimator(multidim)
-    if multidim
-        integrator = MultiDimFixedGKIntegrator([-6.0, -6.0, -6.0], [6.0, 6.0, 6.0])
-        dist = std_mv_normal(3)
-    else
-        integrator = FixedGKIntegrator(-6.0, 6.0)
-        dist = Normal()
-    end
-    return PosteriorAbilityEstimator(dist, integrator)
-end
-
-function prepare_empty(item_bank, actual_responses, ability_tracker)
-    responses = TrackedResponses(BareResponses([], []),
-        item_bank,
-        ability_tracker)
-    (item_bank, actual_responses, responses)
-end
-
-function prepare_0(ability_estimator)
-    (item_bank, question_labels_, abilities_, actual_responses) = dummy_3pl(;
-        num_questions = 100,
-        num_testees = 1)
-    prepare_empty(item_bank, actual_responses, PointAbilityTracker(ability_estimator, NaN))
-end
-
-function prepare_0_mirt(ability_estimator)
-    (item_bank, question_labels_, abilities_, actual_responses) = dummy_mirt_4pl(3;
-        num_questions = 100,
-        num_testees = 1)
-    prepare_empty(item_bank,
-        actual_responses,
-        PointAbilityTracker(ability_estimator, [NaN, NaN, NaN]))
-end
-
-function prepare_50(ability_estimator)
-    (item_bank, question_labels_, abilities_, actual_responses) = dummy_3pl(;
-        num_questions = 100,
-        num_testees = 1)
-    idxs = sample(1:100, 50)
-    responses = TrackedResponses(BareResponses(idxs,
-            actual_responses[idxs, 1]),
-        item_bank,
-        PointAbilityTracker(ability_estimator, NaN))
-    (item_bank, actual_responses, responses)
-end
-
-function run_all(dummy_data, objective)
-    (item_bank, actual_responses, responses) = dummy_data
-    track!(responses)
-    criterion_state = init_thread(objective, responses)
-    for item_idx in eachindex(item_bank)
-        objective(criterion_state, responses, item_idx)
-    end
-end
-
-function run_single(dummy_data, objective)
-    (item_bank, actual_responses, responses) = dummy_data
-    criterion_state = init_thread(objective, responses)
-    objective(criterion_state, responses, 1)
-end
-
-function profile_objective(run_profile::RunProfile,
-        pre_bench::PrepBench,
-        run_bench::RunBench,
-        objective::Objective,
-        ability_estimator) where {RunProfile, PrepBench, RunBench, Objective}
-    dummy_data = pre_bench(ability_estimator)
-    run() = run_bench(dummy_data, objective)
-    @info "init run"
-    run()
-    @info "benchmark run"
-    run_profile(run)
-end
-
-#=
-if isdefined(Profile, :Allocs)
-    run_pprof_allocs = function(run)
-        Profile.Allocs.@profile run()
-        prof = Profile.Allocs.fetch()
-        PProf.Allocs.pprof(prof)
-    end
-end
-=#
-
-function get_cmdline()
-    if Sys.iswindows()
-        String.(split(unsafe_string(ccall(:GetCommandLineA, Cstring, ())), " "))
-    elseif Sys.isapple()
-        String.(split(strip(read(`/bin/ps -p $(getpid()) -o command=`, String)), " "))
-    elseif Sys.isunix()
-        String.(split(read(joinpath("/", "proc", string(getpid()), "cmdline"), String),
-            "\x00";
-            keepempty = false))
-    else
-        j_cmd = String.(split(Base.julia_cmd(), " "))
-        args_joined = join(ARGS, " ")
-        [j_cmd..., PROGRAM_FILE, args_joined...]
-    end
-end
-
-function run_track_allocs(run_bench::F) where {F}
-    Profile.clear_malloc_data()
-    run_bench()
-end
-
-function run_profile(run::F) where {F}
-    Profile.@profile run()
-    prof = Profile.fetch()
-    PProf.pprof(prof)
-end
-
-function run_time(run::F) where {F}
-    @time run()
-end
-
-function run_btime(run_bench::F) where {F}
-    t = @benchmark $(run_bench)() evals=1000 samples=1000
-    dump(t)
-end
-
-function run_statprofilerhtml(run::F) where {F}
-    @profilehtml run()
-end
-
-PROFILERS = Dict("track_allocs" => run_track_allocs,
-    "profile" => run_profile,
-    "time" => run_time,
-    "btime" => run_btime,
-    "profilehtml" => run_statprofilerhtml)
-
-BENCHES = Dict("all0" => (prepare_0, run_all),
-    "allmirt" => (prepare_0_mirt, run_all),
-    "all50" => (prepare_50, run_all),
-    "single50" => (prepare_50, run_single))
-#=
-if isdefined(Profile, :Allocs)
-    PROFILERS["pprof_allocs"] = run_pprof_allocs
-end
-=#
-
-function objective(next_item_rule::NextItemRule)
-    next_item_rule.criterion
-end
-
-function get_next_item_rule(rule_name, ability_estimator)
-    if rule_name == "drule"
-        NextItemRule(DRuleItemCriterion(ability_estimator))
-    else
-        catr_next_item_aliases[rule_name](ability_estimator)
-    end
-end
-
-function main()
-    settings = ArgParseSettings()
-    @add_arg_table settings begin
-        "profiling_mode"
-        help = "The profiling mode to use. Can be 'pprof_allocs', 'track_allocs', 'profile', or 'time'."
-        required = true
-        "next_item_rule"
-        help = "The next item rule to use"
-        required = true
-        "bench"
-        help = "The benchmark to use"
-        required = true
-    end
-    args = parse_args(settings)
-    ability_estimator = get_ability_estimator(args["next_item_rule"] == "drule")
-    point_ability_estimator = ModeAbilityEstimator(ability_estimator)
-    next_item_rule = get_next_item_rule(args["next_item_rule"], point_ability_estimator)
-    if args["profiling_mode"] == "track_allocs" && !haskey(ENV, "TRACK_ALLOCS")
-        cmdline = get_cmdline()
-        insert!(cmdline,
-            findfirst(x -> endswith(x, ".jl"), cmdline),
-            "--track-allocation=all")
-        cmd = Cmd(Cmd(cmdline), env = ("TRACK_ALLOCS" => "TRUE",))
-        @info "Running subprocess to track allocs" cmd
-        Base.run(cmd)
-        return
-    end
-    (pre_bench, run_bench) = BENCHES[args["bench"]]
-    profile_objective(PROFILERS[args["profiling_mode"]],
-        pre_bench,
-        run_bench,
-        objective(next_item_rule),
-        point_ability_estimator)
-end
-
-if abspath(PROGRAM_FILE) == @__FILE__
-    main()
-end
diff --git a/profile/print_mems.jl b/profile/print_mems.jl
deleted file mode 100644
index 22cb033..0000000
--- a/profile/print_mems.jl
+++ /dev/null
@@ -1,3 +0,0 @@
-using Coverage
-
-display(analyze_malloc([ARGS[1]]))
diff --git a/src/Aggregators/slow.jl b/src/Aggregators/slow.jl
deleted file mode 100644
index bda960d..0000000
--- a/src/Aggregators/slow.jl
+++ /dev/null
@@ -1,19 +0,0 @@
-function slow_int_abil_posterior_given_resps{F}(f::F,
-        responses::AbstractVector{Response},
-        items::AbstractItemBank;
-        lo = 0.0,
-        hi = 10.0) where {F}
-    quadgk((θ -> f(θ) * abil_posterior_given_resps(responses, items, θ)), lo, hi, int_tol)[1]
-end
-
-function slow_max_abil_posterior_given_resps(f::Function,
-        responses::AbstractVector{Response},
-        items::AbstractItemBank;
-        lo = 0.0,
-        hi = 10.0)
-    optimize((θ_arr -> -abil_posterior_given_resps(responses, items, first(θ_arr))),
-        lo,
-        hi,
-        NelderMead(),
-        Optim.Options(g_tol = optim_tol))[1]
-end
diff --git a/src/Compat/CatR.jl b/src/Compat/CatR.jl
index c17cb6e..8c6cc56 100644
--- a/src/Compat/CatR.jl
+++ b/src/Compat/CatR.jl
@@ -61,23 +61,6 @@ end
 
 const ability_estimator_aliases = _ability_estimator_aliases()
 
-#=
-        for (resp_exp, resp_exp_nick) in resp_exp_nick_pairs
-            next_item_rule = NextItemRule(
-                ExpectationBasedItemCriterion(resp_exp, AbilityVariance(numtools.integrator, distribution_estimator(abil_est)))
-            )
-            next_item_rule = preallocate(next_item_rule)
-            est_next_item_rule_pairs[Symbol("$(abil_est_str)_mepv_$(resp_exp_nick)")] = (abil_est, next_item_rule)
-            next_item_rule = NextItemRule(
-                ExpectationBasedItemCriterion(resp_exp, InformationItemCriterion(abil_est))
-            )
-            next_item_rule = preallocate(next_item_rule)
-            est_next_item_rule_pairs[Symbol("$(abil_est_str)_mei_$(resp_exp_nick)")] = (abil_est, next_item_rule)
-        end
-        est_next_item_rule_pairs[Symbol("$(abil_est_str)_mi")] = (abil_est, InformationItemCriterion(abil_est))
-=#
-
-
 function setup_integrator(lo=-4.0, hi=4.0, pts=33)
     Integrators.MidpointIntegrator(range(lo, hi, pts))
 end
diff --git a/src/NextItemRules/NextItemRules.jl b/src/NextItemRules/NextItemRules.jl
index 0016f19..edec020 100644
--- a/src/NextItemRules/NextItemRules.jl
+++ b/src/NextItemRules/NextItemRules.jl
@@ -64,6 +64,12 @@ export ObservedInformationPointwiseItemCriterion
 export RawEmpiricalInformationPointwiseItemCriterion
 export EmpiricalInformationPointwiseItemCriterion
 
+public PointwiseNextItemRule, PointwiseFirstNextItemRule
+public WeightedStateMultiCriterion, WeightedItemMultiCriterion
+public GreedyForcedContentBalancer
+public PosteriorExpectedKLInformationItemCriterion
+public alt_expected_1d_item_information, alt_expected_mirt_item_information, alt_expected_mirt_3pl_item_information
+
 # Prelude
 include("./prelude/abstract.jl")
 include("./prelude/next_item_rule.jl")
diff --git a/src/NextItemRules/criteria/pointwise/information_support.jl b/src/NextItemRules/criteria/pointwise/information_support.jl
index 5f4dd30..6442e32 100644
--- a/src/NextItemRules/criteria/pointwise/information_support.jl
+++ b/src/NextItemRules/criteria/pointwise/information_support.jl
@@ -30,42 +30,6 @@ function log_resp(ir::ItemResponse{<:CdfMirtItemBank}, val, θ)
     end
 end
 
-#=
-# XXX: Not sure if this is optimal numerically or speed wise -- possibly it
-# would be better to just transform to linear space in this case?
-@inline function log_transform_irf_y(guess, slip, y)
-    # log space version of guess + irf_size(guess, slip) * y
-    logaddexp(log(guess), log(irf_size(guess, slip)) + y)
-end
-
-@inline function log_transform_irf_y(ir::ItemResponse{<:GuessItemBank}, response, y)
-    guess = y_offset(ir.item_bank, ir.index)
-    if response
-        log_transform_irf_y(guess, 0.0, y)
-    else
-        log_transform_irf_y(0.0, guess, y)
-    end
-end
-
-@inline function log_transform_irf_y(ir::ItemResponse{<:SlipItemBank}, response, y)
-    slip = y_offset(ir.item_bank, ir.index)
-    if response
-        log_transform_irf_y(0.0, slip, y)
-    else
-        log_transform_irf_y(slip, 0.0, y)
-    end
-end
-
-function log_resp_vec(ir::ItemResponse{<:AnySlipOrGuessItemBank}, θ)
-    r = log_resp_vec(inner_item_response(ir), θ)
-    SVector(log_transform_irf_y(ir, false, r[1]), log_transform_irf_y(ir, true, r[2]))
-end
-
-function log_resp(ir::ItemResponse{<:AnySlipOrGuessItemBank}, val, θ)
-    log_transform_irf_y(ir, val, log_resp(inner_item_response(ir), val, θ))
-end
-=#
-
 log_resp(ir::ItemResponse{<:GuessAndSlipItemBank}, response, θ) = log(resp(ir, response, θ))
 log_resp(ir::ItemResponse{<:GuessAndSlipItemBank}, θ) = log(resp(ir, θ))
 log_resp_vec(ir::ItemResponse{<:GuessAndSlipItemBank}, θ) = log.(resp_vec(ir, θ))
diff --git a/src/NextItemRules/criteria/pointwise/kl.jl b/src/NextItemRules/criteria/pointwise/kl.jl
index efaf115..a19e7eb 100644
--- a/src/NextItemRules/criteria/pointwise/kl.jl
+++ b/src/NextItemRules/criteria/pointwise/kl.jl
@@ -12,6 +12,9 @@ struct PosteriorExpectedKLInformationItemCriterion{
     DistributionEstimatorT <: DistributionAbilityEstimator,
     IntegratorT <: AbilityIntegrator
 } <: PointwiseItemCriterion
+    point_estimator::PointEstimatorT
+    distribution_estimator::DistributionEstimatorT
+    integrator::IntegratorT
 end
 
 function PosteriorExpectedKLInformationItemCriterion(bits...)
diff --git a/src/NextItemRules/porcelain/aliases.jl b/src/NextItemRules/porcelain/aliases.jl
deleted file mode 100644
index e69de29..0000000
diff --git a/src/NextItemRules/strategies/random.jl b/src/NextItemRules/strategies/random.jl
index 4f5965d..8d2ad2d 100644
--- a/src/NextItemRules/strategies/random.jl
+++ b/src/NextItemRules/strategies/random.jl
@@ -10,18 +10,6 @@ administered.
     rng::RandomT = Xoshiro()
 end
 
-#=
-function get_rng(bits...)
-    @returnsome find1_instance(AbstractRNG, bits)
-    @returnsome find1_type(AbstractRNG, bits) typ -> typ()
-    Xoshiro()
-end
-
-function RandomNextItemRule(bits...)
-    RandomNextItemRule(rng=get_rng(bits...))
-end
-=#
-
 function best_item(rule::RandomNextItemRule, responses::TrackedResponses, items)
     # TODO: This is not efficient
     item_idxes = Set(1:length(items))
diff --git a/src/Stateful.jl b/src/Stateful.jl
index f8482e6..c5621cd 100644
--- a/src/Stateful.jl
+++ b/src/Stateful.jl
@@ -155,32 +155,6 @@ model backing the CAT.
 """
 function item_response_functions end
 
-## Running the CAT
-function Sim.run_cat(cat_config::CatLoop{RulesT},
-        ib_labels = nothing) where {RulesT <: StatefulCat}
-    (; stateful_cat, get_response, new_response_callback) = cat_config
-    while true
-        next_index = next_item(stateful_cat)
-        next_label = item_label(ib_labels, next_index)
-        @debug "Querying" next_index next_label
-        response = get_response(next_index, next_label)
-        @debug "Got response" response
-        add_response!(stateful_cat, next_index, response)
-        terminating = termination_condition(responses, item_bank)
-        if new_response_callback !== nothing
-            new_response_callback(get_responses(responses), terminating)
-        end
-        if terminating
-            @debug "Met termination condition"
-            break
-        end
-    end
-    return (
-        get_responses(stateful_cat),
-        get_ability(stateful_cat)
-    )
-end
-
 ## TODO: Materialise the cat into a decsision tree
 
 """