The Global Centre for Risk and Innovation (GCRI)
A research protocol fixes, before data are collected, what a study asks, how it will answer and what would count as an answer: the hypotheses, the design, the controls, the outcomes, the sample and the analysis. Many failures of credibility trace back to a protocol that was vague, unwritten or changed after the data were seen. This page sets out how protocols are built, registered, reviewed and reported, and what ethics committees, editors and funders rely on when they accept a study's claims.
Research protocols · Labs · Quarter 3
| PR-378 sensor drift | Field experiment | Yes | Approved | Running |
| PR-705 AI triage | Randomised | Yes | Conditions | Setup |
| PR-694 message recall | Survey experiment | Yes | Approved | Complete |
| PR-360 heat exposure | Cohort | No | Pending | Draft |
Fig.Protocol and replication board. Design wireframe with placeholder names and illustrative values, not a record or a live system.
A research protocol is the plan that fixes, before data are collected, what a study asks, how it will answer and what would count as an answer: hypotheses, design, controls, outcomes, sample and analysis. Many failures of credibility trace back to protocols that were vague, unwritten or changed after the data were seen.
For research protocols, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, land cover and night lights, framed on World; every other NASA layer, live feed and forecast waits in the layer list.
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For research protocols, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, land cover and night lights, framed on World; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
Layers and dates
Hypotheses, controls and scientific acceptance. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
When outcomes, exclusions, covariates or stopping rules are chosen after the data are seen, many analyses become possible and the most striking one tends to be reported. Each choice looks reasonable alone; together they inflate false positives and effect sizes.
A missing control, unblinded assessment or non-random allocation lets something other than the intervention explain the difference. Design flaws cannot be repaired by analysis; they travel into every result and review built on the study.
Small samples miss real effects, and the effects they do detect tend to be overestimated. Underpowered studies that reach significance seed literatures that later, larger replications cannot match.
Protocols change for good reasons, such as slow recruitment or a safety signal. When a change is not dated, explained and reported, readers cannot tell a justified amendment from outcome switching, and reviews pool what should not be pooled.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Preregistration | Recording a study's hypotheses, design and analysis plan in a public registry before data collection or analysis. |
| Registered report | A format in which a journal peer reviews and accepts a study's protocol before results are known. |
| Reporting guideline | A checklist, such as CONSORT or PRISMA, listing what a study report must include, collected by the EQUATOR Network. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Registration before data collection | percent of studies with a time-stamped registration | annual | Trial and study registries | OFFICIAL |
| Primary outcome consistency | percent of reports matching the registered primary outcome | annual | Registry and publication comparison | OBSERVED |
| Sample size justification | percent of protocols with a power or precision rationale | annual | Protocol audit | OBSERVED |
| Reporting guideline adherence | percent of applicable checklist items reported | per study | Assessment against CONSORT, PRISMA, ARRIVE or STROBE | ESTIMATED |
| Protocol amendments | count per study, each with a stated reason | per study | Registry history and ethics committee records | OFFICIAL |
| Registered report availability | number of journals offering the format | annual | Center for Open Science journal list | REPORTED |
| Results posting timeliness | months from primary completion to posted results | per study | Trial registries | OFFICIAL |
| Randomisation and blinding reported | percent of eligible studies | annual | Risk-of-bias assessments | ESTIMATED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| OSF Registries (Center for Open Science) | Time-stamped preregistrations and registered report protocols across disciplines | Open, licence per registration |
| ClinicalTrials.gov (US National Library of Medicine) | Registered trials, protocol change history and posted results | Public domain |
| WHO International Clinical Trials Registry Platform | Search across primary national trial registries | Free, WHO terms of use |
| PROSPERO (NIHR) | Registered protocols for systematic reviews | Free access, terms of use |
| protocols.io | Versioned, citable step-by-step laboratory and field methods | Open, CC BY for public protocols |
| EQUATOR Network library | Reporting guidelines by study design, with extensions | Free access, licence per guideline |
| Crossref metadata | Links between registrations, articles, corrections and funders | Open metadata, no restrictions |
Nexus Labs prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Research ethics committees and institutional review boards | Whether a protocol's risks, consent and design justify approval, and whether an amendment needs fresh review | Complete protocol, sample size rationale, amendment history with reasons |
| Journal editors | Whether to accept a registered report in principle, or whether a submitted analysis matches its plan | Time-stamped registration compared line by line with the manuscript |
| Research funders | Whether a proposal's design can answer its question before money is committed | Power or precision rationale, control conditions, data management plan |
| Medicines and device regulators | Whether trial evidence was generated under the protocol submitted to them | Registry history, deviation logs, results posting record |
Every experiment involves choices: which observations to exclude, which covariates to adjust for, which time window to use. Each choice may be reasonable alone, but when they are made after seeing the data, the number of possible analyses grows quickly and one of them will usually show something. This is the problem methodologists call analytic flexibility, and it is a central reason why published effects often shrink or vanish when repeated.
Interdisciplinary work adds its own drivers. Disciplines differ in what they treat as a control, how they handle missing data and what level of evidence they expect. A hydrologist, an economist and an epidemiologist may each consider a design rigorous by their own standard while disagreeing about what it shows. A protocol forces those differences into the open before work starts.
Incentives matter too. Positive, novel findings are easier to publish and fund, which rewards flexibility and penalises null results. Pre-registration and registered reports are the main structural responses.
A time-stamped record of hypotheses and analysis plans. It limits post hoc changes but cannot stop a poorly chosen question.
Estimates how much data is needed to detect a meaningful effect, using probability and statistics. It depends on assumed effect sizes that are often uncertain.
Randomisation, difference-in-differences, regression discontinuity and instrumental variables from causal inference. Each rests on assumptions that must be stated and, where possible, tested.
Pre-agreed thresholds for when a method, model or prototype is considered to work. They make success testable but can be gamed if set too loosely.
A protocol cannot make a bad measurement good or fix a biased sample. Deviations from protocol are permitted when justified, but are reported with their reasons.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.