audit_disagreements     Surface strong LLM-human disagreements for a
                        manual audit
backend_mock            Mock backend for tests
backend_ollama          Ollama backend
build_prompt            Build a screening prompt for one record
check_setup             Verify local setup for 'screenllm'
clear_cache             Clear cached LLM scores for a project
custom_ensemble         Define a custom LLM ensemble
default_ensemble        The paper's default LLM ensemble
default_ensemble_light
                        A "light" ensemble that runs on a laptop
define_criteria         Define screening inclusion criteria
delete_artefact         Delete an artefact (or a whole project)
delete_model            Delete an Ollama model to free up disk space
detect_gpu              Detect a usable GPU for Ollama inference
estimate_runtime        Estimate wall-clock time for a ranking run
export_report           Render the screening report as a self-contained
                        HTML document
export_worksheet        Export the human-screening worksheet
find_duplicates         Detect and remove duplicate records
gpu_status              Live NVIDIA GPU status snapshot
install_prereqs         One-stop setup for a fresh machine
launch_app              Launch the full end-to-end Shiny app
launch_screening_app    Launch the interactive screening Shiny app
list_project_artefacts
                        Canonical artefact filenames
list_projects           List existing project names
load_artefact           Load an artefact from a project directory
load_toy_cbfm_criteria
                        Load the ready-made criteria for the toy CBFM
                        corpus
ollama_catalog          Curated catalog of Ollama models useful for
                        screening
ollama_health           Ping the Ollama server
ollama_installed_models_detail
                        Installed Ollama models with disk-space
                        metadata
plan_screening          Plan the human screening set with the SAFE
                        stopping rule
pull_model              Pull an Ollama model to the local server
rank_records            Rank a corpus with an LLM ensemble
read_decisions          Read completed screening decisions
read_records            Read a corpus of records from disk
save_artefact           Save an artefact into a project directory
summarise_screening     Summarise a completed screening session
