GCRI · Systems Science and Modelling
Methods and uncertainty
The methods Systems Science and Modelling relies on: their equations and assumptions, the data they need, how they are validated and the limits of what they can show.
The workspace for methods and uncertainty.
Evidence register
Systems science · Methods and uncertainty · Example interface, not a record
Indicators
unit · cadence · label
| Models in library | models | monthly | Published statistics | SP-9504 |
| Models with validation record | of models | monthly | DERIVED | SP-6894 |
| Coupled runs completed | runs | weekly | OBSERVED | SP-0370 |
| Reuse across platforms | uses | quarterly | DERIVED | SP-3045 |
Source passport
- Source
- Model library
- Licence
- open · attribution
- Steward
- Research partner
- Coverage
- 94 pct of places
- Known limits
- sparse in uplands
Coverage by place
Systems Science and Modelling · Evidence register. Evidence register: example names and illustrative values, not a record.
The methods in use.
- 01Systems engineeringRequirements for decision models · Interface control for coupled modelsApplied here
- 02Probability and statisticsBayesian calibration · Proper scoring of predictions · Ensemble statisticsApplied here
- 03Uncertainty quantification and model validationUncertainty budgets · Surrogate models for expensive simulations · Credibility assessmentApplied here
- 04Network science and contagionCommon network representations · Contagion model comparison · Multilayer analysisApplied here
- 05Complex systems and agent-based modellingAgent-based model standards · Feedback and tipping point analysis · Early warning indicatorsApplied here
- 06Optimisation and operations researchProblem formulation guidance · Robust and stochastic comparisons · Solver benchmarkingApplied here
- 07Decision analysis under uncertaintyFraming the decision before the model · Value of information for modelsApplied here
- 08High-performance, cloud and edge computingEnsemble design within budgets · Workflow orchestration · Reproducible environmentsApplied here
Each method, its role in this field and how it is checked.
- Systems engineeringRole hereSystems engineering is the method this platform stewards for the network.Checks appliedRequirements traceability; Interface review; Change impact analysis
- Probability statisticsRole hereProbability and statistics are the language of uncertainty in modelling.Checks appliedPosterior predictive checks; Prior sensitivity; Scoring on held-out data
- Uncertainty quantificationRole hereUncertainty quantification and model validation is a method this platform stewards.Checks appliedEmulator validation; Interval coverage; Structural comparison
- Network scienceRole hereNetwork science and contagion is a method this platform stewards for the network.Checks appliedMissing link sensitivity; Model comparison; Event validation
- Complex systemsRole hereComplex systems and agent-based modelling is a method this platform stewards.Checks appliedPattern-oriented validation; Robustness of tipping points; False alarm assessment
- OptimisationRole hereOptimisation and operations research is a method this platform stewards.Checks appliedFormulation review; Solution verification; Out-of-sample testing
- Decision analysisRole hereDecision analysis under uncertainty connects models to choices.Checks appliedDecision relevance review; Sensitivity of choice; Communication testing
- ComputingRole hereHigh-performance, cloud and edge computing determine which models can be run, how many ensemble members and scenarios are feasible, and whether results can be reproduced.Checks appliedCross-platform reruns; Resource accounting; Failure recovery testing
How the process runs.
Process explorer · Process
Methods and uncertainty: PRISMA 2020 review reporting
10 steps·4 stages
Process
Methods and uncertainty: PRISMA 2020 review reporting
PRISMA 2020 is a reporting guideline for systematic reviews; the steps follow its checklist, not a mandated sequence, and no Nexus document adopts it.
01 Plan
- 01Registration and protocolRecord · The review teamThe guideline asks for registration details, access to the protocol and any amendments.
- 02Eligibility criteriaRecord · The review teamThe guideline asks for the inclusion and exclusion criteria and how studies were grouped.
02 Find and select
- 03Search: sources and strategiesStep · The review teamThe guideline asks for the information sources and the full search strategies. It does not fix which sources are used.
- 04Selection of studiesStep · The review teamThe guideline asks how studies were judged eligible, including how many reviewers screened. It does not fix the number of reviewers.
- 05Flow diagramRecordThe flow diagram shows the number of records found, the number of studies included and the reasons for exclusion.
03 Analyse
- 06Data collectionStep · The review teamThe guideline asks how data were collected from reports and which data items were sought.
- 07Risk of biasStep · The review teamThe guideline asks for the methods and tools used to assess risk of bias.
- 08SynthesisModel · The review teamThe guideline asks for the effect measures and the synthesis methods. It does not prescribe meta-analysis.
- 09Certainty of evidenceStep · The review teamThe guideline asks for the methods used to assess certainty, and reports the result per outcome. It does not name a grading scale.
04 Report
- 10Review reportRecordThe guideline helps authors report why the review was done, what they did and what they found.
ReportsOutline of an externally published reporting guideline, not a Nexus process and not a record of operation. PRISMA 2020 mainly covers reviews of intervention effects. No Nexus page names it. Every programme is at service level R0.
Where uncertainty in systems modelling analysis comes from, and how it is shown.
| Source | Why it matters here | How it is reported |
|---|---|---|
| Coupling | Interfaces between models introduce inconsistencies | Interface assumptions documented |
| Structural | Different models disagree | Intercomparison |
| Parameters | Many are poorly constrained | Sensitivity analysis |
| Scenarios | Deep uncertainty | Scenario discovery |
How uncertainty is reported.
- 01
State assumptions
Each analysis lists its assumptions and the data it depends on.
- 02
Quantify where possible
Ranges and confidence are reported alongside central estimates.
- 03
Validate and compare
Models are checked against observations and, where possible, against other models.
- 04
Publish limits
What an analysis cannot show is stated beside what it can.
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Are the methods open?
Contribute evidence from this page.
Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
- EmailGateway GW-GCRISend it from this pageEvidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.
- ZenodoOpen depositDeposit it and submit to the communityPublish your own record on Zenodo with your ORCID iD, then submit it to the Reports community there. Curators review it; the DOI stays yours.
- ReportsGCRISee every way to contributeThe contribution types, how each is reviewed, what credit you receive, the licence and what is never accepted.
Never send personal data, sensitive infrastructure detail or anything you have no right to share. A contribution is reviewed before use; sending it confers no authorship or editorial rights, and sponsorship never buys a finding.
Bring a method, a dataset or a question.
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