From rigorous methodology to flexible execution, built for Big Five research.
From versioned IPIP-NEO-120 scoring to reproducible exports and transparent QC flags, b5lab helps research teams move from collection to analysis with confidence.
From raw responses to analysis-ready evidence
- 1Versioned IPIP-NEO-120 scoringEach completed session stores scoring version, domain totals, and facet totals for citation-ready traceability.
- 2Transparent quality control flagsSpeeding, straightlining, invariance, and missingness are computed at completion to support explicit inclusion criteria.
- 3Reproducible export packageExports include codebook metadata, QC policy context, and exclusion reasons so methods teams can reproduce decisions.
Scientific evidence layer
Methodological rigor built into the product surface
Rigor is implemented as product behavior: versioned scoring, explicit QC signals, and exports that preserve analytical context.
Standardized IPIP-NEO-120 scoring pipeline
Participant completion automatically computes domain and facet totals with explicit scoring version tags for downstream citation and traceability.
Built-in data quality screening
Completed sessions include automated speeding, straightlining, invariance, and missingness checks to support transparent exclusion logic.
Reproducible exports for analysis teams
Exports carry scoring versions, QC thresholds, and item metadata so statistics and methods teams can reproduce decisions consistently.
Analysis-ready inclusion recommendations
Rows include `include_in_analysis` and explicit exclusion reasons, reducing manual preprocessing effort before modeling.
Research workflow flexibility
Design collection workflows without sacrificing methodological control
Combine recruitment flexibility, entitlement guardrails, and role boundaries in one workspace while keeping scientific outputs consistent.
Entitlement-aware study operations
Session starts, access-code generation, and exports are guarded by plan and credit checks to prevent silent operational drift.
Flexible recruitment modes
Run anonymous studies for broad intake or tokenized studies when cohort eligibility and controlled distribution are required.
Institution and lab role boundaries
Institution admins, billing admins, viewers, and lab operators can collaborate with explicit responsibilities.
What research teams get
Capabilities that protect data quality and delivery speed
Domain-aware onboarding controls
Institutional domains can self-serve workspace setup while claimed domains route members through moderated join requests.
Predictable entitlement guardrails
Credits, seats, and lab limits stay visible so teams can plan capacity before research operations are blocked.
Role-specific governance controls
Separate billing authority and study operations using institution admin, billing admin, viewer, and lab-level roles.
Anonymous and tokenized participant access
Manage controlled cohorts with access-code generation, claim, revoke, and expiry workflows in the same product surface.
Reproducible exports with metadata context
Export JSON and CSV with item codebook, scoring version, facet/domain totals, QC policy, and exclusion reasons.
Quality and trait analytics workspace
Explore quality breakdowns, trait distributions, demographics, and session trends with study-scoped filtering.
Research execution flow
Three steps from setup to defensible analysis
Configure study and recruitment policy
Create an IPIP-NEO-120 study, choose locale, and select anonymous or tokenized participant recruitment.
Collect sessions with explicit QC checks
Completion computes domain/facet scoring plus speeding, straightlining, invariance, and missingness QC flags.
Export reproducible analysis package
Download JSON/CSV exports with scoring version, QC policy metadata, exclusion reasons, and multilingual codebook context.
Start your first study
Need rigorous psychometrics with operational flexibility?
Begin with a trial for eligible institutional domains or submit request access for reviewed onboarding.