Create a compact Gazepoint methods section — create_gazepoint_methods

Generate conservative, manuscript-ready methods text from available Gazepoint workflow objects. The function reports workflow structure and audit coverage only; it does not infer emotion, stress, cognition, preference, diagnosis, mechanism, or exact temporal onset from biometric or gaze-linked signals.

Usage

create_gazepoint_methods_section(
  export_profile = NULL,
  design_audit = NULL,
  event_audit = NULL,
  condition_audit = NULL,
  decision_log = NULL,
  package_version = as.character(utils::packageVersion("gpbiometrics")),
  validation = NULL,
  include_guardrails = TRUE
)

Arguments

export_profile: Optional object from profile_gazepoint_export_folder().
design_audit: Optional object from audit_gazepoint_experiment_design().
event_audit: Optional object from audit_gazepoint_event_coverage().
condition_audit: Optional object from audit_gazepoint_condition_balance().
decision_log: Optional object from create_gazepoint_analysis_decision_log().
package_version: Package version to report. Defaults to the installed gpbiometrics version.
validation: Optional named list with validation entries, for example list(test = "PASS 2322", check = "0 errors, 0 warnings, 0 notes").
include_guardrails: Logical. If TRUE, append conservative interpretation guardrails.

Value

A character vector with class "gazepoint_report_text".

Examples

log <- create_gazepoint_analysis_decision_log(study_id = "demo")
create_gazepoint_methods_section(decision_log = log)
#> Gazepoint biometric workflow processing was conducted using gpbiometrics 2.0.0, an R package designed for importing, checking, preprocessing, summarising, and reporting Gazepoint Biometrics and GP3-derived biometric exports.
#> 
#> Workflow decisions were recorded in a structured analysis decision log. The log contained 0 decision record(s), covering exclusions, preprocessing choices, quality-control decisions, analysis settings, or reviewer-facing notes where applicable.
#> 
#> All biometric, gaze-linked, and time-course outputs were treated as workflow descriptors. They were not interpreted as direct measures of emotion, stress, cognition, preference, health status, diagnosis, mechanism, or precise temporal onset.