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Record W4386554066 · doi:10.1002/9781119781042.ch1

Introduction

2023· other· en· W4386554066 on OpenAlexaff
Anwer Al‐Dulaimi, Octavia A. Dobre, I Chih‐Lin

Bibliographic record

VenueBlockchains · 2023
Typeother
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsMemorial University of NewfoundlandExfo Electro-Optical Engineering (Canada)
Fundersnot available
KeywordsBlockchainDatabase transactionComputer securityComputer scienceLedgerCryptocurrencyDecentralizationTransparency (behavior)HackerSingle point of failureBusinessComputer networkDatabaseFinance

Abstract

fetched live from OpenAlex

Blockchain technology continues to emerge as one of the most revolutionary developments of the digital transformation era. This technology has the potential to transform industries by creating a new decentralized platform for securely storing, sharing, and exchanging data. The most important feature of blockchain technology is its decentralization and ability to associate users with precise security policies. Unlike traditional systems that rely on a centralized authority, the blockchain operates on a distributed network of computational units that work together to validate transactions. This means that there is no single point of failure, and the system is resistant to hacking and cyberattacks. Additionally, blockchain is a secure platform that ensures the integrity of every single transaction across the network. Transactions are validated by a network of computers, and once validated, they are recorded on the ledger permanently. The immutable nature of the blockchain ledger ensures that it remains unaltered and undeletable. This feature makes the blockchain ideal for storing sensitive data, such as financial records, medical records, and personal information. The security of the blockchain is one of the reasons why it has become a popular technology in the financial industry, and it is an interesting area of study for those interested in developing secure systems. Another important feature of the blockchain is its transparency. All transactions on the blockchain are public and can be viewed by anyone on the network. This means that there is no need for a central authority to verify transactions, and users can trust the system without the need for intermediaries. Then, the smart self-executing contracts that are programmed on the blockchain. They are triggered by specific events and can automatically execute transactions without the need for intermediaries. These blockchain features are introducing innovative use cases across multiple industries that were previously impossible to implement. In this chapter, we will discuss the motivation for widespread adoption of blockchains, opportunities for innovation, applied industrial use cases, and how some of those ideas are presented in this book chapters.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.395
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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