MétaCan
Menu
Back to cohort
Record W4392864062 · doi:10.3390/challe15010015

Bitcoin Use Cases: A Scoping Review

2024· review· en· W4392864062 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChallenges · 2024
Typereview
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This scoping review examines individual and societal use cases of Bitcoin in the peer-reviewed literature. Arksey and O’Malley’s scoping review methodology was used, and a comprehensive search strategy was employed using Web of Science and Engineering village databases. Articles were screened at the title and abstract and full-text levels by the authors. One author conducted data extraction to summarize the data. In total, 17 relevant articles were included in this review. Investment and savings were the most widely reported use cases at an individual level, with payments and international transfers less frequently reported in the studies. Only two studies reported on societal use cases of legal tender; however, only one country, El Salvador, executed its intention. Our study suggests that Bitcoin is being used by individuals around the world with little report of societal (e.g., country adoption) uses cases. For example, there is evidence on the internet and on a grass-roots level that Bitcoin is being used in circular economies; however, the peer-reviewed literature may not yet capture the extent and full benefits and challenges. As such, we provide ideas for future research to more comprehensively explore Bitcoin uses and its impacts on individuals and society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.729
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.208
GPT teacher head0.400
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it