Turns criticism into executable counterexamples and discriminating experiments, and organizes candidates as research-programme sequences through provenance, re-instantiation, null models, paired bets, anomalies and question genomes.
Philosophy
Criticism should change testable predictions, and programmes should be compared through new predictions and settled outcomes.
Architecture & control flow
- 01
Generate provenance-bearing candidates and apply PG discrimination checks
- 02
Create paired settleable bets for competing explanations
- 03
Turn anomalies into repair obligations and new questions
- 04
Use L1/L2/L3 repairs on lemmas, definitions or programmes
- 05
Compare programme progress and reallocate budgets
Architecture outline derived from this version’s control flow.
What this version changes
Connects refutation, anomalies, agendas and programmes while limiting template self-promotion.
Inputs & outputs
- Inputs
Candidate topics, provenance records, discriminating experiments and anomalies.
- Outputs
Provenance gates, paired bets, anomaly ledgers, question lists, programme states and budget allocations.
Implementation & evidence scope
Default candidates and some anomalies/settlements remain synthetic smoke cases; provenance fields or two copies do not establish independent external generation. Its strength is protocol structure and conservative downgrading.
Code & bundled material
The introduction draws on bundled notes, changelogs and central code. Software tests, synthetic diagnostics and scientific effectiveness use different evidence standards.
Source references
pyproject.toml· 1–5V6_4_LAKATOS_DESIGN.md· 3–22harness/discovery_v64/pipeline_v64.py· 1–7harness/discovery_v64/pipeline_v64.py· 71–111harness/discovery_v64/pipeline_v64.py· 191–229harness/discovery_v64/verifier_v64/pg_gates.py· 23–62V6_4_LAKATOS_CHANGELOG.md· 19–26