% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/orm_autodim.R
\name{orm_autodim}
\alias{orm_autodim}
\title{Automatic dimension extraction and risk cross-matrix}
\usage{
orm_autodim(
  mx,
  method = "blocks",
  text_col = "abstract",
  n_dims = 12L,
  min_freq = 3L,
  max_doc_pct = 0.35,
  min_cooccur = 0.5,
  fuzzy_sim = 0.85,
  stopwords = NULL,
  lang = getOption("orisma.lang", "en"),
  verbose = getOption("orisma.verbose", TRUE)
)
}
\arguments{
\item{mx}{An \code{orisma_matrix} object from \code{\link[=orm_extract]{orm_extract()}}.}

\item{method}{Character. \code{"blocks"} (default) or \code{"text"}.}

\item{text_col}{Character. Text field for \code{method = "text"}. Default \code{"abstract"}.}

\item{n_dims}{Integer. Max dimensions for \code{method = "text"}. Default \code{12}.}

\item{min_freq}{Integer. Min document frequency for \code{method = "text"}. Default \code{3}.}

\item{max_doc_pct}{Numeric (0-1). Max document proportion for \code{method = "text"}.
Terms above this are too generic. Default \code{0.35}.}

\item{min_cooccur}{Numeric (0-1). Min co-occurrence with a risk. Default \code{0.5}.}

\item{fuzzy_sim}{Numeric (0-1). Fuzzy grouping threshold. Default \code{0.85}.}

\item{stopwords}{Character vector. Extra stopwords for \code{method = "text"}.}

\item{lang}{Character. \code{"en"} or \code{"es"}.}

\item{verbose}{Logical.}
}
\value{
A list (class \code{orisma_dims}) ready for \code{\link[=orm_dim_matrix]{orm_dim_matrix()}}.
}
\description{
\code{orm_autodim()} automatically discovers the most relevant contextual
dimensions of a corpus using two complementary modes:

\strong{Mode 1: Dictionary blocks} (default, \code{method = "blocks"})
Uses the normative blocks of the ORISMA dictionary (A-Safety, B-Hygiene,
C-Ergonomics, D-Psychosociology, E-Biological, F-Emerging) as dimensions.
Computes a block x block co-occurrence matrix showing how many studies
address combinations of risk blocks simultaneously. Works for any corpus
without any configuration.

\strong{Mode 2: Free text} (\code{method = "text"})
Extracts discriminant terms from abstracts using TF-IDF-like filtering.
Useful for discovering domain-specific dimensions not covered by the
dictionary (e.g. specific materials, sectors, tasks).
}
\seealso{
\code{\link[=orm_dim_matrix]{orm_dim_matrix()}}
}
