Scientific evidence
Measurements, station and regional coverage, descriptive calculations, source records and stated limitations are the evidence available for review.
Current execution status
No external generative AI output was used in the current scientific assessment.
The current This Air Quality Project run uses deterministic acquisition, normalisation, quality-control, freshness, linkage and communication rules. Configured AI credentials or catalogue entries do not constitute model execution or scientific evidence.
Automated publication authority: no. Human review required: yes.
Known sources54
Identified sites19
Fresh sites0
Configured joins11
Permitted roles
- Suggest source-discovery queries and candidate datasets for human approval.
- Assist metadata normalisation and document/entity extraction with deterministic validation against originals.
- Rank evidence-review workload using transparent, reproducible features.
- Draft bounded summaries that are checked against the frozen public release contract.
- Propose anomaly candidates only when deterministic statistical gates independently reproduce them.
Prohibited roles
- Causal source attribution or source-apportionment determination.
- Permit, legal, regulatory or compliance determination.
- Exposure, safety, medical or health-impact determination.
- Inventing, repairing or replacing missing measurements.
- Granting website, email, social or scientific-publication authority.
- Treating model confidence, fluent text or credential availability as validation.
Controlled analytics roadmap
Each capability remains disabled for scientific inference until its minimum gate and evaluation requirements are met.
| Priority | Capability | Method | Minimum gate |
|---|---|---|---|
| 1 | data-latency and missingness diagnostics | deterministic lateness baselines and change-point alerts by provider, station and pollutant | timestamp provenance, stable expected cadence and alert evaluation on historical outages |
| 2 | robust anomaly candidate detection | seasonal robust statistics with multiplicity control, never a single uncalibrated black-box score | fresh quality-eligible series, station-role compatibility and out-of-sample false-alert evaluation |
| 3 | spatiotemporal episode clustering | distance/time constrained clustering followed by independent meteorology and competing-source checks | multiple physical sites, synchronized timestamps and documented spatial uncertainty |
| 4 | document and register extraction | schema-constrained extraction with page-level citations, hashes and human verification | original authoritative document retained and every extracted field traceable to source location |
| 5 | regional-model residual screening | compare compatible ground observations with CAMS or equivalent model context without treating residuals as attribution | unit, averaging period, grid, time and uncertainty compatibility established |
evidence assurance provenance
Assurance receipt: 0feb0feb48f360876c6446bfef727616a3f8fb29178519ae386c3c7ad122ecd9
All current inputs are listed with presence, size and SHA-256 identity in assets/data/ai-ml-assurance.json.
AI or ML may assist retrieval, triage and drafting only under frozen evidence, deterministic checks and human review. It cannot establish source contribution, causation, compliance, exposure, safety or health effects.
Scientific evidence and software assurance are different
Engineering assurance
Automated checks confirm that the pipeline followed its declared rules. They do not constitute peer review, accreditation, regulatory approval or institutional endorsement.