# Citedby.in in the Machine Relations Index

Canonical URL: https://machinerelations.ai/index/domains/citedby.in
Canonical domain: citedby.in
Source role: Other observed source
Release mri_score_v2.1+2026-10-26+ff67a630fa8e; methodology mri_score_v2.1; generated 2026-10-26; window 2026-05-10 to 2026-10-26; artifact b37ddb40c879.

citedby.in appeared as a cited source in 1 of 31,659 monitored answer runs (0.00%) from 2026-05-10 to 2026-10-26.

## Overall Evidence

- Citation rate: 0.00%
- Cited runs: 1 of 31,659
- Days cited: 1 of 163
- Engine breadth: 1 observed engines (chatgpt)
- Confidence: Collecting
- Standing: collecting · 0.00% across 1/31,659 observed runs

## Observed Segments

| Category | Question shape | State | Cited runs | Observed runs | Run dates | Rate | Standing |
|---|---|---|---:|---:|---:|---:|---|
| [AI Visibility & GEO](https://machinerelations.ai/index/categories/ai-visibility-geo) | [Is it worth it](https://machinerelations.ai/index/categories/ai-visibility-geo/is_x_worth) | published | 1 | 284 | 12 | 0.35% | #395 of 684 |

## Citation Record

citedby.in has been cited in one monitored answer run, on October 4, 2026, by ChatGPT, in answers to AI Visibility & GEO / Is it worth it questions. Other sources cited for AI Visibility & GEO questions: https://machinerelations.ai/index/categories/ai-visibility-geo

## Peers

Citedby.in holds its best segment rank, #395 of 684, in AI Visibility & GEO / Is it worth it, at 0.35%. 363 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/ai-visibility-geo/is_x_worth

| Rank | Source | Source role | Segment citation rate | Against this source |
|---|---|---|---:|---|
| #221 of 684 | [Business Insider](https://machinerelations.ai/index/domains/businessinsider.com) | Editorial publication | 0.70% | +0.35 pts |
| #222 of 684 | [Campbelldigitalstudio.com](https://machinerelations.ai/index/domains/campbelldigitalstudio.com) | Other observed source | 0.70% | +0.35 pts |
| #223 of 684 | [Chad-wyatt.com](https://machinerelations.ai/index/domains/chad-wyatt.com) | Other observed source | 0.70% | +0.35 pts |
| #224 of 684 | [Clearscope.io](https://machinerelations.ai/index/domains/clearscope.io) | Other observed source | 0.70% | +0.35 pts |
| #225 of 684 | [Cognizo.ai](https://machinerelations.ai/index/domains/cognizo.ai) | Other observed source | 0.70% | +0.35 pts |
| #226 of 684 | [Conbersa.ai](https://machinerelations.ai/index/domains/conbersa.ai) | Other observed source | 0.70% | +0.35 pts |
| #394 of 684 | [Citebeam.ai](https://machinerelations.ai/index/domains/citebeam.ai) | Other observed source | 0.35% | Same rate |
| #396 of 684 | [Citeinai.com](https://machinerelations.ai/index/domains/citeinai.com) | Other observed source | 0.35% | Same rate |

## Citation

Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. Citedby.in (citedby.in), 0.00% citation rate, 1 of 31,659 monitored answer runs, 2026-05-10 to 2026-10-26. Release mri_score_v2.1+2026-10-26+ff67a630fa8e. https://machinerelations.ai/index/domains/citedby.in. CC BY 4.0.

APA

Parrott, J. (2026). Citedby.in (citedby.in) in the Machine Relations Index (Version mri_score_v2.1+2026-10-26+ff67a630fa8e) [Data set]. Machine Relations Research. https://machinerelations.ai/index/domains/citedby.in https://doi.org/10.5281/zenodo.23652423

BibTeX

```bibtex
@misc{parrott2026mricitedbyin,
  author = {Parrott, Jaxon},
  title = {Citedby.in (citedby.in) in the Machine Relations Index},
  year = {2026},
  version = {mri\_score\_v2.1+2026-10-26+ff67a630fa8e},
  publisher = {Machine Relations Research},
  url = {https://machinerelations.ai/index/domains/citedby.in},
  doi = {10.5281/zenodo.23652423},
  license = {CC-BY-4.0},
  note = {Machine Relations Index (MRI) by Jaxon Parrott, 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/citedby.in/badge.svg

[![Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. Citedby.in (citedby.in), 0.00% citation rate, 1 of 31,659 monitored answer runs, 2026-05-10 to 2026-10-26. Release mri_score_v2.1+2026-10-26+ff67a630fa8e. https://machinerelations.ai/index/domains/citedby.in. CC BY 4.0.](https://machinerelations.ai/index/domains/citedby.in/badge.svg)](https://machinerelations.ai/index/domains/citedby.in)

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 is the citation above.

## 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)