Summary | Pipeline overview | Why exact reproduction of the ANZECC & ARMCANZ 2000 guideline input data is not possible | What can be approximated | Filtering approach: concentrationused | Structural differences between the 2000 and 2016 databases | Endpoint harmonisation between 2016 and 2000 | Chemical identifier resolution and CAS parent grouping | cas_parent_lookup | Grouped identifier columns | Chemical identifiers available post-mapping | Reference Data for 2016 Toxicity Values | Reference Resolution Strategy | Coverage | SSD eligibility workflow | 1. Base filters | 2. Test type classification and priority selection | 3. ACR conversion for retained acute records | 4. Geometric mean concentration per species × endpoint | 5. Most sensitive endpoint selection | 6. Minimum species and taxonomic group threshold | 7. Nesting | DGV matching | Purpose | Name-based CAS fallback | DGV matching summary | Remaining unmatched chemicals | References

Purpose | Executable source | Inputs | Method | Step 1 — Extract distinct 2016 endpoint labels | Step 2 — Normalise labels | Step 3 — Two-stage mapping to 2000 codes | Step 4 — Output | Outputs | How the lookup is used in the main pipeline | Outcomes (v2 refined) | Remaining unmapped labels | Notes

Overview | Comparing posterior toxicity values | Comparing posterior fitted values

Models in bayesnec | Parameter definitions | Model types for NEC and EC~x~ estimation | Model suitability for response types | Model definitions | EC~x~ models | ecxlin | ecxexp | ecxsigm | ecx4param | ecxwb1 | ecxwb1p3 | ecxwb2 | ecxwb2p3 | ecxll5 | ecxll4 | ecxll3 | ecxhormebc5 | ecxhormebc4 | NEC models | neclin | nec3param | nec4param | nechorme | nechormepwr | neclinhorme | nechorme4 | nechorme4pwr | nechormepwr01 | necsigm | References

bayesnec | Examples | Fitting multiple models and model averaging using the bnec function | Fitting a bnec model | Exploring a bayesmanecfit model | Extracting toxicity values | Putting it all together | References

Overview | Default priors in bayesnec | Priors for response-scaled parameters | Priors for predictor-scaled parameters | Priors for other parameters | User specified priors | bayesnecfit | bayesmanecfit

cmdstanr installation workflow | 1. Install Rtools | 2. Install git | 3. Intall cmdstan | 4. Test cmdstan in R studio | Compile a model | Run a model using brms | References

bayesnec | Background | Installation | Examples | Fitting the nec4param model using bnec | Binomial data | Beta-Binomial | Beta data | Poisson data | Negative binomial | Measure data | References