create_gazepoint_model_card: Create a governance-focused model card

In gp3ml: Governance-First Predictive Modelling for 'Gazepoint' Research

Create a governance-focused model card

Description

Create a governance-focused model card

Usage

create_gazepoint_model_card(
  model,
  intended_use,
  evaluation = NULL,
  calibration = NULL,
  feature_manifest = NULL,
  external_validation = NULL,
  limitations = character(),
  ethical_review = NULL
)

Arguments

model	A fitted gp3ml_model object.
intended_use	Explicit description of the intended research use.
evaluation	Optional performance-evaluation object.
calibration	Optional calibration-assessment object.
feature_manifest	Optional feature-provenance manifest.
external_validation	Optional external-validation result.
limitations	Character vector describing model limitations.
ethical_review	Optional ethical-review information.

Value

A gp3ml_model_card object containing task, model, governance, evaluation, calibration, provenance, external-validation, and limitation metadata.

Examples

training_data <- data.frame(
  participant_id = rep(sprintf("P%02d", 1:12), each = 2),
  trial_id = sprintf("T%02d", 1:24),
  stimulus_id = rep(c("S01", "S02"), 12),
  fixation_duration = 180 + seq_len(24),
  pupil_change = sin(seq_len(24) / 3),
  stringsAsFactors = FALSE
)
training_data$quality_status <- factor(
  c(
    "pass", "review", "pass", "review", "review", "pass",
    "review", "pass", "pass", "review", "review", "pass",
    "review", "pass", "review", "pass", "pass", "review",
    "pass", "review", "review", "pass", "pass", "review"
  ),
  levels = c("pass", "review")
)
task <- declare_gazepoint_task(
  data = training_data,
  outcome = "quality_status",
  purpose = "Predict predefined recording-quality review status",
  task_type = "classification",
  unit_id = "trial_id",
  participant_id = "participant_id",
  stimulus_id = "stimulus_id",
  generalization_target = "new_participants",
  positive = "review"
)
model <- train_gazepoint_classifier(
  data = training_data,
  task = task,
  predictors = c("fixation_duration", "pupil_change"),
  engine = "glm",
  seed = 101L
)
card <- create_gazepoint_model_card(
  model = model,
  intended_use = paste(
    "Support manual review of predefined",
    "recording-quality status"
  ),
  limitations = "Synthetic example for documentation."
)
card

gp3ml documentation built on Aug. 23, 2026, 5:11 p.m.