--- title: "3logic.ru in the Machine Relations Index" description: "Canonical domain: 3logic.ru" canonical: "https://machinerelations.ai/index/domains/3logic.ru" --- # 3logic.ru in the Machine Relations Index Canonical URL: https://machinerelations.ai/index/domains/3logic.ru Canonical domain: 3logic.ru Source role: Other observed source Release mri_score_v2.1+2026-11-06+4a9cac5e2d8d; methodology mri_score_v2.1; generated 2026-11-06; window 2026-05-10 to 2026-11-06; artifact ccf757103126. 3logic.ru appeared as a cited source in 1 of 36,708 monitored answer runs (under 0.01%) from 2026-05-10 to 2026-11-06. ## Overall Evidence - Citation rate: under 0.01% - Cited runs: 1 of 36,708 - Days cited: 1 of 174 - Engine breadth: 1 observed engine (chatgpt) - Confidence: Collecting - Standing: Collecting: no rank until it clears the evidence floor ## Observed Segments | Category | Question shape | State | Cited runs | Observed runs | Run dates | Rate | Standing | |---|---|---|---:|---:|---:|---:|---| | [Deep Tech & Hardware](https://machinerelations.ai/index/categories/deep-tech-hardware) | [Top lists](https://machinerelations.ai/index/categories/deep-tech-hardware/top_list) | published | 1 | 267 | 13 | 0.37% | #242 of 428 | ## Citation Record 3logic.ru has been cited in one monitored answer run, on November 6, 2026, by ChatGPT, in answers to Deep Tech & Hardware / Top lists questions. Other sources cited for Deep Tech & Hardware questions: https://machinerelations.ai/index/categories/deep-tech-hardware ## Peers 3logic.ru holds its best segment rank, #242 of 428, in Deep Tech & Hardware / Top lists, at 0.37%. 187 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/deep-tech-hardware/top_list | Rank | Source | Source role | Segment citation rate | Against this source | |---|---|---|---:|---| | #178 of 428 | [3dmag.com](https://machinerelations.ai/index/domains/3dmag.com) | Editorial publication | 0.75% | +0.38 pts | | #179 of 428 | [acroname.com](https://machinerelations.ai/index/domains/acroname.com) | Other observed source | 0.75% | +0.38 pts | | #180 of 428 | [aerowint.com](https://machinerelations.ai/index/domains/aerowint.com) | Other observed source | 0.75% | +0.38 pts | | #181 of 428 | [aiaa.org](https://machinerelations.ai/index/domains/aiaa.org) | Academic and government source | 0.75% | +0.38 pts | | #182 of 428 | [aifitlab.com](https://machinerelations.ai/index/domains/aifitlab.com) | Other observed source | 0.75% | +0.38 pts | | #183 of 428 | [arrow.com](https://machinerelations.ai/index/domains/arrow.com) | Other observed source | 0.75% | +0.38 pts | | #240 of 428 | [vibimglobal.com](https://machinerelations.ai/index/domains/vibimglobal.com) | Other observed source | 0.75% | +0.38 pts | | #244 of 428 | [aerospherepower.com](https://machinerelations.ai/index/domains/aerospherepower.com) | Other observed source | 0.37% | Same rate | ## Citation Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. 3logic.ru, under 0.01% citation rate, 1 of 36,708 monitored answer runs, 2026-05-10 to 2026-11-06. Release mri_score_v2.1+2026-11-06+4a9cac5e2d8d. https://machinerelations.ai/index/domains/3logic.ru. CC BY 4.0. APA Parrott, J. (2026). 3logic.ru in the Machine Relations Index (Version mri_score_v2.1+2026-11-06+4a9cac5e2d8d) [Data set]. Machine Relations Research. https://machinerelations.ai/index/domains/3logic.ru https://doi.org/10.5281/zenodo.23652423 BibTeX ```bibtex @misc{parrott2026mri3logicru, author = {Parrott, Jaxon}, title = {3logic.ru in the Machine Relations Index}, year = {2026}, version = {mri\_score\_v2.1+2026-11-06+4a9cac5e2d8d}, publisher = {Machine Relations Research}, url = {https://machinerelations.ai/index/domains/3logic.ru}, 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/3logic.ru/badge.svg [![3logic.ru in the Machine Relations Index: cited in under 0.01% of monitored AI answers (1 of 36,708 runs), Nov 6, 2026 release. Machine Relations Research.](https://machinerelations.ai/index/domains/3logic.ru/badge.svg)](https://machinerelations.ai/index/domains/3logic.ru) Put this badge on your site to show how often AI answers cite it. It links to this profile and updates with every new release; if a later release no longer includes this domain, the badge stops loading. To keep today's numbers fixed, save the SVG and host it yourself. ## 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)