% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/classes.R, R/delta_lsi.R
\docType{class}
\name{LeakSplits-class}
\alias{LeakSplits-class}
\alias{LeakFit-class}
\alias{LeakAudit-class}
\alias{LeakDeltaLSI-class}
\alias{show,LeakDeltaLSI-method}
\title{S4 Classes for bioLeak Pipeline}
\usage{
\S4method{show}{LeakDeltaLSI}(object)
}
\arguments{
\item{object}{A \code{\linkS4class{LeakDeltaLSI}} object.}
}
\value{
An S4 object of the respective class.
}
\description{
These classes capture splits, model fits, and audit diagnostics produced by
\code{make_split_plan()}, \code{fit_resample()}, and \code{audit_leakage()}.
}
\section{Slots}{

\describe{
\item{\code{mode}}{Splitting mode. One of "subject_grouped", "batch_blocked",
"study_loocv", "time_series", or "combined".}

\item{\code{indices}}{List of resampling descriptors (train/test indices when available)}

\item{\code{info}}{(LeakSplits) Metadata associated with the split plan (mode, coldata, hash, etc.)}

\item{\code{splits}}{A [`LeakSplits`] object used for resampling}

\item{\code{metrics}}{Model performance metrics per resample}

\item{\code{metric_summary}}{Summary of metrics across resamples}

\item{\code{audit}}{Audit information per resample}

\item{\code{predictions}}{List of prediction objects}

\item{\code{preprocess}}{Preprocessing steps used during fitting}

\item{\code{learners}}{Learner definitions used in the pipeline}

\item{\code{outcome}}{Outcome variable name}

\item{\code{task}}{Modeling task name}

\item{\code{feature_names}}{Feature names included in the model}

\item{\code{info}}{(LeakFit) Metadata about the model fit (sample IDs, timings, provenance, etc.)}

\item{\code{fit}}{A [`LeakFit`] object used to generate the audit}

\item{\code{permutation_gap}}{Data frame summarising permutation gaps}

\item{\code{perm_values}}{Numeric vector of permutation-based scores}

\item{\code{batch_assoc}}{Data frame of batch associations}

\item{\code{target_assoc}}{Data frame of feature-wise outcome associations}

\item{\code{duplicates}}{Data frame detailing duplicate records}

\item{\code{trail}}{List capturing audit trail information}

\item{\code{info}}{(LeakAudit) Metadata about the audit (mechanism summary, settings, provenance, etc.)}

\item{\code{metric}}{Performance metric compared between pipelines}

\item{\code{exchangeability}}{Exchangeability assumption used for the sign-flip test}

\item{\code{tier}}{Inference tier label based on effective number of repeats}

\item{\code{strict}}{Whether strict mode was requested}

\item{\code{R_eff}}{Effective number of paired repeats available for inference}

\item{\code{delta_lsi}}{Huber-robust point estimate of repeat-level metric difference}

\item{\code{delta_lsi_ci}}{BCa 95\% CI for delta_lsi (NA when R_eff < 10)}

\item{\code{delta_metric}}{Arithmetic mean of repeat-level metric differences}

\item{\code{delta_metric_ci}}{BCa 95\% CI for delta_metric (NA when R_eff < 10)}

\item{\code{p_value}}{Sign-flip randomization test p-value (NA when R_eff < 5 or unpaired)}

\item{\code{inference_ok}}{TRUE when tier A (R_eff >= 20, paired, finite p and CI)}

\item{\code{folds_naive}}{Per-fold data frame for the naive pipeline}

\item{\code{folds_guarded}}{Per-fold data frame for the guarded pipeline}

\item{\code{repeats_naive}}{Per-repeat aggregate data frame for the naive pipeline}

\item{\code{repeats_guarded}}{Per-repeat aggregate data frame for the guarded pipeline}

\item{\code{info}}{(LeakDeltaLSI) Metadata including R_naive, R_guarded, paired status, and block details}
}}

\seealso{
[make_split_plan()], [fit_resample()], [audit_leakage()]

[fit_resample()]

[audit_leakage()], [audit_report()]

[delta_lsi()]
}
