The full walkthrough · 001–006

How Littview works.

A systematic literature review has a well-defined shape: search, screen, extract, synthesize, report. Littview follows that shape exactly — every stage below is a real part of the product, not a marketing simplification.

001 / IMPORT

Start with your search results, not a blank spreadsheet.

Upload your exports directly — Littview reads BibTeX, RIS, PubMed MEDLINE, and EndNote XML, or you can bring in a Zotero library. Thousands of references import in a single batch.

In the product

Four supported formats — BibTeX, RIS, PubMed, EndNote XML
Zotero library import
Batch import in the thousands
Malformed entries flagged — never silently dropped

Drag & drop your library files

or click to browse

.bib.ris.txt · PubMed.xml · EndNote

LibrariesReferencesDuplicate DetectionDuplicate References

References

Algorithmic management and worker autonomy: a systematic map

Okafor, T. · 2022 · J. Bus. Psychol.

Adoption of AI-enabled recruitment: an UTAUT extension

Keller, M. · 2024 · Comput. Hum. Behav.

Library health

5,112Total referencesall imported

5,112Valid referencesready to screen

Libraries

Total References: 5,112

Upload Library

pubmed_search PubMed

1,847 references.

scopus_export.ris RIS

1,626 references.

wos_results.bib BibTeX

1,204 references.

endnote_lib.xml EndNote XML

435 references.

Process References

Validate and add references from your uploaded libraries to this project.

Process References

Processing complete — 5,112 references added.

002 / DEDUPLICATE

Find the duplicates your search strategy created.

Multi-database searches always produce overlapping results. Littview scans every reference for likely duplicates, lets you tune how strict the matching is, and shows you each group side by side before anything is merged.

In the product

Similarity-based detection
Adjustable threshold, 70–100%
Auto-resolve above threshold (Pro) or manual review
Nothing merged without a resolution

Duplicate Detection

Run Again

Found 214 duplicate group(s) across 462 references.

Primary

Revillod, G.

Exploring the acceptability of artificial intelligence in human resources management

2025

Duplicate groups

Group 212 · 2 records

Resolved · primary kept

Group 213 · 2 records

Resolved · primary kept

Group 215 · 3 records

Pending review

Pending ReviewAuto-Resolvable

Revillod, Guillaume

Exploring the acceptability of AI in human resources management

202597% similar

This study looks at perceptions of AI systems in HR management within Swiss organisations, based on a survey experiment provided to 324 HR professionals…

Set as primaryMark as duplicateNot a duplicate

Duplicates Auto Resolver

Similarity Threshold90%

Higher values mean stricter matching for auto-resolving duplicates

Auto Resolve

Auto Resolution Preview

Auto-Resolvable

177

86% of pending

Manual Review

14% of pending

003 / SCREEN

Screen against your criteria, with AI backing your judgment.

Define your criteria once, distribute papers automatically, and screen at keyboard speed. AI checks each title and abstract against your criteria — and, if you choose, your past decisions — returning include/exclude, a confidence score, and the criteria behind it. The decision stays yours.

In the product

Reusable criteria library
Automatic distribution across reviewers
Keyboard-shortcut screening
AI confidence scores that learn from your decisions
Optional full-text escalation

My screening queue

Adoption of AI-enabled recruitment: an UTAUT extension

Keller, M. · 2024

Pending

Algorithmic management and worker autonomy

Okafor, T. · 2022

Pending

Exclusion Criteria0 selected

E2 — Sample size < 100

Underpowered studyCase report

Inclusion Criteria3 selected

PopulationSelected

✦Adult workforce✦HR professionals

InterventionSelected

✦AI-based HR toolTraditional HRIS

Paper 214 of 1,038 · Your queueAI Applied

Exploring the acceptability of artificial intelligence in human resources management

This study looks at perceptions of AI systems in HR management within Swiss organizations, based on a survey experiment provided to 324 private and public HR professionals. It explores how UTAUT’s predictors influence the acceptability of four different types of AI HR tools…

ExcludeEResetSIncludeI

AI SuggestionInclude

Confidence

91%

Reasoning

Survey of 324 HR professionals evaluating four AI-based HR tools — population, intervention and outcome criteria all supported.

Based on the paper’s title and abstract — attached PDFs are not analyzed.

004 / RESOLVE CONFLICTS

Disagreements don’t get lost — they get resolved.

When reviewers disagree on a paper, it’s automatically routed to a dedicated conflict workspace showing every vote, note, and PDF highlight side by side. AI can propose a resolution with its reasoning; the final call is always a human one.

In the product

Automatic conflict detection
One workspace with full context
AI-assisted resolution
Full audit trail

Screening conflicts

Perceptions of algorithmic fairness in hiring decisions

2 reviews · 1v1 split

Conflict

Chatbot-assisted onboarding and employee trust

2 reviews · 1v1 split

Conflict

Notes & highlights

“Solid instrument, but check the sample — is n large enough for subgroup claims?”Marco Rinaldi · note

a survey experiment provided to 324 private and public HR professionalsDana Whitfield · highlight · p.4

Threshold settings

Inclusion threshold50%

Papers at or above the threshold are included; ties become conflicts

Conflict

Exploring the acceptability of artificial intelligence in human resources management

1 Include (50%)1 Exclude (50%)of 2 reviews

Threshold: 50%

Reviewer Decisions

Dana Whitfield

Population + intervention criteria met; n = 324

Include

Marco Rinaldi

Worried the sample is too small for E2

Exclude

Resolution note (optional)

Add a note explaining your decision…

IncludeExclude

AI RecommendationInclude

Confidence

87%

Reasoning

Both notes cite sample size. Exclusion E2 (n < 100) does not apply — n = 324. The population, intervention and outcome criteria are supported by both reviewers’ highlights. Recommend include.

Processed in 2.1s · Sees both votes, notes & highlights — the final call is yours.

005 / EXTRACT

Pull structured data out of PDFs, not by hand.

Build a custom extraction form — text, numbers, dropdowns, multi-select, yes/no — and let AI pre-fill it from the source PDF, field by field, with every answer linked to the exact passage it came from. Add a second-reviewer verification pass for anything that needs it.

In the product

Custom field types
AI pre-fill with evidence mapping
PDF annotation while extracting
Optional verifier role
Reusable extraction templates

My extraction queue

Paper 12 of 84 · in progress

Revillod (2025)

6 / 8 fields

Keller (2024)

Pending

Okafor (2022)

Pending

Revillod_2025_AI_HR.pdf · p.4 · Methods

Based on the theoretical framework outlined above, we designed our empirical approach. A survey experiment was provided to 324 private and public HR professionals in Swiss organizations. Respondents were randomly assigned to one of four vignettes, each describing an AI-based HR tool in a realistic deployment scenario…

Randomized design✓ 91%

YesNo

Primary outcome

Behavioural intention (BI) to use AI-based HR tools

Extraction form · your templatePaper 12 of 84

Sample size✓ 93%

n = 324 HR professionals

❝ Extractedp.4·Methods

A survey experiment was provided to 324 private and public HR professionals in Swiss organizations.

Study design83%

Cross-sectional

Inferredno direct statement

Single measurement wave, no follow-up mentioned — consistent with a cross-sectional survey design.

AI ExtractionRe-extract

Stats:6 extracted·1 inferred·1 manual·100% complete

Field indicators:AI-filled·❝ ExtractedInferred

Every value stays editable — click a field to see its passage in the PDF.

006 / REPORT

Leave with a written report, not just a spreadsheet.

The PRISMA 2020 flow diagram is computed directly from your screening and extraction records — every number in it traces back to a recorded decision. A sortable, filterable evidence table covers every included study, and AI drafts the Methods and Results sections from the same data, with numbered citations that resolve to your included studies.

In the product

Auto-computed PRISMA 2020 diagram, DOCX export
Evidence table with CSV export
AI-drafted Methods & Results with citations + references list
DOCX export of the report

Export

Methods · generated Jul 20

Two reviewers independently screened each record against the predefined criteria; disagreements were resolved in a dedicated conflict workspace with AI-assisted recommendations…

Results synthesis ready

The AI Results draft for “AI in HR Management — SLR” is ready to review.

Evidence Table·82 of 84 papers shown1 filter activeDesign: Survey ×

Search across all fields…

Study↕Sample↕DesignPrimary outcome

Revillod (2025)n = 324Cross-sectionalBehavioural intention

Keller (2024)n = 512SurveyAdoption

Okafor (2022)n = 1,306Mixed methodsTrust in algorithms

Moreno & Tan (2023)n = 89Case studyPerceived fairness

One row per included study — sortable, filterable, CSV export. Stars mark your key papers.

Results Synthesis · DraftRegenerate

Across the 84 included studies, questionnaire-based designs dominated (61/84) [12], and UTAUT was the most common framework (n = 27) [3, 9]. Sample sizes ranged from 42 to 1,306 participants [7, 21]; behavioural intention to use was the most frequently reported outcome (58/84) [3, 14, 27].

References

[3] Keller et al. (2024) · Comput. Hum. Behav.

[9]Moreno & Tan (2023) · Int. J. Inf. Manag.

[12] Okafor et al. (2022) · J. Bus. Psychol.

…

Copy TextExport DOCX

Synthesized from your extraction data — exports state their “Data coverage” plainly.

Ready when your search is

See it on your own references.

Import a real search export and take it as far as you like — the free plan covers a full solo pass.

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