---
title: "Budgetsheethub.blog in the Machine Relations Index"
description: "Canonical domain: budgetsheethub.blog"
canonical: "https://machinerelations.ai/index/domains/budgetsheethub.blog"
---

# Budgetsheethub.blog in the Machine Relations Index

Canonical URL: https://machinerelations.ai/index/domains/budgetsheethub.blog
Canonical domain: budgetsheethub.blog
Source role: Other observed source
Release mri_score_v2.1+2026-11-04+94f24cb38da0; methodology mri_score_v2.1; generated 2026-11-04; window 2026-05-10 to 2026-11-04; artifact b397502c0e39.

budgetsheethub.blog appeared as a cited source in 1 of 35,834 monitored answer runs (0.00%) from 2026-05-10 to 2026-11-04.

## Overall Evidence

- Citation rate: 0.00%
- Cited runs: 1 of 35,834
- Days cited: 1 of 172
- Engine breadth: 1 observed engines (perplexity)
- Confidence: Collecting
- Standing: collecting · 0.00% across 1/35,834 observed runs

## Observed Segments

| Category | Question shape | State | Cited runs | Observed runs | Run dates | Rate | Standing |
|---|---|---|---:|---:|---:|---:|---|
| [Consumer Finance](https://machinerelations.ai/index/categories/consumer-finance) | [Is it worth it](https://machinerelations.ai/index/categories/consumer-finance/is_x_worth) | published | 1 | 295 | 13 | 0.34% | #246 of 421 |

## Citation Record

budgetsheethub.blog has been cited in one monitored answer run, on October 27, 2026, by Perplexity, in answers to Consumer Finance / Is it worth it questions. Other sources cited for Consumer Finance questions: https://machinerelations.ai/index/categories/consumer-finance

## Peers

Budgetsheethub.blog holds its best segment rank, #246 of 421, in Consumer Finance / Is it worth it, at 0.34%. 203 sources on that leaderboard share that rate, and their order inside the tie is not a measured difference. Listed here: the nearest sources cited more and less often than it, and the sources beside it that share this best segment. Leaderboard: https://machinerelations.ai/index/categories/consumer-finance/is_x_worth

| Rank | Source | Source role | Segment citation rate | Against this source |
|---|---|---|---:|---|
| #157 of 421 | [Bart.gov](https://machinerelations.ai/index/domains/bart.gov) | Academic and government source | 0.68% | +0.34 pts |
| #158 of 421 | [Betterbuyer.com](https://machinerelations.ai/index/domains/betterbuyer.com) | Other observed source | 0.68% | +0.34 pts |
| #159 of 421 | [Budgetpeer.com](https://machinerelations.ai/index/domains/budgetpeer.com) | Other observed source | 0.68% | +0.34 pts |
| #160 of 421 | [Business.com](https://machinerelations.ai/index/domains/business.com) | Other observed source | 0.68% | +0.34 pts |
| #161 of 421 | [Bytestart.co.uk](https://machinerelations.ai/index/domains/bytestart.co.uk) | Other observed source | 0.68% | +0.34 pts |
| #162 of 421 | [Centage.com](https://machinerelations.ai/index/domains/centage.com) | Other observed source | 0.68% | +0.34 pts |
| #245 of 421 | [Budgetingapp.io](https://machinerelations.ai/index/domains/budgetingapp.io) | Other observed source | 0.34% | Same rate |
| #247 of 421 | [Burtonwealth.com](https://machinerelations.ai/index/domains/burtonwealth.com) | Other observed source | 0.34% | Same rate |

## Citation

Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. Budgetsheethub.blog (budgetsheethub.blog), 0.00% citation rate, 1 of 35,834 monitored answer runs, 2026-05-10 to 2026-11-04. Release mri_score_v2.1+2026-11-04+94f24cb38da0. https://machinerelations.ai/index/domains/budgetsheethub.blog. CC BY 4.0.

APA

Parrott, J. (2026). Budgetsheethub.blog (budgetsheethub.blog) in the Machine Relations Index (Version mri_score_v2.1+2026-11-04+94f24cb38da0) [Data set]. Machine Relations Research. https://machinerelations.ai/index/domains/budgetsheethub.blog https://doi.org/10.5281/zenodo.23652423

BibTeX

```bibtex
@misc{parrott2026mribudgetsheethubblog,
  author = {Parrott, Jaxon},
  title = {Budgetsheethub.blog (budgetsheethub.blog) in the Machine Relations Index},
  year = {2026},
  version = {mri\_score\_v2.1+2026-11-04+94f24cb38da0},
  publisher = {Machine Relations Research},
  url = {https://machinerelations.ai/index/domains/budgetsheethub.blog},
  doi = {10.5281/zenodo.23652423},
  license = {CC-BY-4.0},
  note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai}
}
```

DOI: https://doi.org/10.5281/zenodo.23652423

Citation file: https://machinerelations.ai/CITATION.cff

## Badge

Badge image: https://machinerelations.ai/index/domains/budgetsheethub.blog/badge.svg

[![Budgetsheethub.blog in the Machine Relations Index: 0.00% cited in monitored answer runs, 1 of 35,834 runs · Collecting. Machine Relations Research.](https://machinerelations.ai/index/domains/budgetsheethub.blog/badge.svg)](https://machinerelations.ai/index/domains/budgetsheethub.blog)

The badge is live: it shows the current release, so it changes when the release changes, and it returns 404 if this domain leaves the released population. The link goes to this profile, and the alt text says what the badge shows.

## Use the data

The public JSON is https://machinerelations.ai/data/machine-relations-index.json. The release manifest is https://machinerelations.ai/data/mri-release-manifest.json. The domain CSV is https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv. The Zenodo concept DOI is https://doi.org/10.5281/zenodo.23652423.

```bash
curl -fsSL "https://machinerelations.ai/data/machine-relations-index.json" -o machine-relations-index.json
curl -fsSL "https://machinerelations.ai/data/mri-release-manifest.json" -o mri-release-manifest.json
curl -fsSL "https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv" -o domains.csv
curl -fsSL -L "https://doi.org/10.5281/zenodo.23652423" -o mri-zenodo.html
```

```python
import json
from urllib.request import urlopen

index_url = "https://machinerelations.ai/data/machine-relations-index.json"
with urlopen(index_url) as response:
    index = json.load(response)
print(index["generated"], index["total_domains"])
```

## Public Boundary

The public dataset reports citation rates, rankings, and evidence counts. It excludes internal query identifiers, raw cited URLs, and answer-engine provider payloads. MRI measures observed root-domain citations in monitored prompts; it does not measure all AI answers, recommendation quality, website traffic, or commercial performance. A citation does not prove source support, and MRI confidence is not an Answer-Source Fidelity grade.

## Related Sources

- [Machine Relations Index](https://machinerelations.ai/index)
- [Public JSON artifact](https://machinerelations.ai/data/machine-relations-index.json)
- [Release manifest](https://machinerelations.ai/data/mri-release-manifest.json)