Machine Relations Index Report, September 23, 2026: Healthcare Services publishes as forecast, and 27 community-platform domains still out-lead 1,266 editorial publications

In the September 23, 2026 release of the Machine Relations Index (mri_score_v2.0+2026-09-23), community and social platforms hold or share first place in 26 of the 93 published category-and-question segments, the same absolute count as five days earlier even though the published-segment universe grew by eight. Those 26 first places come from 27 domains, 0.12% of the 23,280 domains the Index has ever seen cited. The single most-cited domain across all six engines is still reddit.com, now at a 12.39% citation rate over 2,042 answer runs in a window that has grown to 130 days, and it is still cited by Gemini, Google AI Mode, Google AI Overviews and Perplexity, and still by neither ChatGPT nor Claude.

This is the second edition of the weekly Index Report. The first edition, published September 18, named five Healthcare Services buyer-question segments as nearest to publication and said the next edition would carry their first leaders if sampling continued on cadence. It did: Healthcare Services now publishes leaders for best tools, how buyers choose, is it worth it, problem-first research and top lists, five segments that were collecting a week ago. Every figure below is taken from the public JSON release at machinerelations.ai/data/machine-relations-index.json, generated 2026-09-23, window 2026-05-10 to 2026-09-23.

The release at a glance #

A segment is one subject category paired with one question shape. The six buyer shapes are best tools (best_x), how buyers choose (how_choose), is it worth it (is_x_worth), problem-first research (problem_first), top lists (top_list) and comparisons (x_vs_y); seven categories also carry a longer-running news-shaped segment (news_topic). A citation rate is the share of a segment's observed answer runs in which at least one engine cited the domain.

The ten most-cited domains across the whole Index, and what moved #

Rates are measured over all 16,475 observed runs, so they read lower than any single segment's rate. Reddit, YouTube and LinkedIn have not moved position across five daily releases. The only rank change in the top ten is Gartner falling two places while TechRadar and G2 each moved up one; Gartner still gained runs cited (454 to 456) but grew more slowly than the two domains that passed it. Per-domain profiles for every ranked domain are published under machinerelations.ai/index/domains.

Healthcare Services publishes as forecast #

The first edition named Healthcare Services as the category nearest to crossing the evidence floor: five buyer-question segments sitting at 78 to 102 observed runs, six of seven required run dates. Five days and one more run date later, four of those five have published (best tools, how buyers choose, is it worth it, problem-first) and a fifth (top lists) is included in the count; only the comparison shape (x_vs_y) is still collecting, at 102 runs across 6 run dates.

Across all Healthcare Services segments combined, nih.gov leads the category overall at a 17.7% citation rate over 1,144 runs, ahead of fiercehealthcare.com at 10.7%. It is the one category in this release where an academic and government source outright leads, not just places second, and the pattern held in both the buyer-question segments and the older news segment.

Who leads each category, shortlist shape against objection shape #

The Index's standing finding is that the question shape, not the outlet's authority, decides which class of source an engine cites. Fourteen categories now publish both the shortlist question (best tools) and the objection question (is it worth it), one more than the thirteen in the first edition.

Reddit leads or shares the objection question in seven of fourteen categories and never leads the shortlist question head-to-head against a vendor or editorial domain except in Deep Tech & Hardware and Education & Training. Cybersecurity remains the clearest vendor-led category on both shapes.

First place by source class, all 93 published segments #

Counting each segment's first-place domain by source role, and crediting every domain tied on rate:

Community platforms hold their 26-segment lead from the first edition even though eight more segments published in between, and they do it with 27 domains against 1,266 editorial publications and 19,667 unclassified long-tail domains. On a per-domain basis a community platform is cited 162.4 times across the Index on average, fifteen times the 10.8 of an editorial publication and forty-five times the 3.6 of an unclassified domain. The unclassified class is the Index's largest population by domain count, 84.5% of all 23,280 cited domains, but it accounts for 54.5% of citation events, so its per-domain rate stays the lowest of any class even as its raw citation total leads. Reading share of citations against share of the domain population, not against share of segments, is what separates a concentrated source class from a merely large one.

Where the six engines differ #

Nineteen of the twenty-five most-cited domains in the Index are cited by all six engines. The exceptions, unchanged in kind from the first edition, are the engine story of this release.

At 130 days and 16,475 runs this pattern has now held across both editions: the two Google surfaces and Gemini cite Reddit and Facebook and ChatGPT and Claude do not; the same two Google surfaces are the only ones that do not cite TechRadar. The release records per-engine presence in the window, whether each engine was observed citing the domain at least once, not a per-engine rate; a per-engine citation rate is not part of the public view and is not inferred here.

What the Index cannot yet say #

Coverage is 93 of 151 measurable segments, up from 85. Of the 58 still collecting, a smaller share now has zero observed runs than in the first edition; HR & Talent remains the next category to watch, with its buyer-question segments still short of the seven-run-date floor. A zero-run segment says the query basket has not sampled that category yet, not that engines behave any particular way there.

Movement since the previous release #

The cited-domain universe grew by 1,101 domains, 5.0%, over the five daily releases between the two edition dates, with growth accelerating in the final two days. Observed runs rose from 15,782 to 16,475 and citation events from 124,397 to 129,264 over the same span, while published segments rose from 85 to 93.

Method notes #

The Index observes six answer engines against a fixed basket of eligible buyer and research queries across 24 measured subject categories plus a legacy news bucket. Every domain an engine cites is measured on equal terms; membership in any external catalog is recorded as a label and never used to decide what is scored. A segment publishes only after 10 observed runs across 7 distinct run dates. The methodology is described in full at machinerelations.ai/index and the release contract at machinerelations.ai/machine-relations-index.md. The engine set follows each provider's own published crawling and citation documentation: OpenAI's crawler documentation, Google Search Central on AI features, Anthropic's crawler documentation and Perplexity's crawler documentation.

FAQ #

What is the Machine Relations Index Report? A weekly reading of the daily public release of the Machine Relations Index: segment leaders, engine differences, coverage and movement, each figure tied to a release id so it can be re-checked.

What changed between the first and second editions? The published-segment count rose from 85 to 93 of 151, led by Healthcare Services crossing the evidence floor on four buyer-question segments as the first edition forecast. Community platforms held their 26-segment lead with only 27 domains, and the top ten most-cited domains saw one rank swap: TechRadar and G2 each passed Gartner.

Does a first-place domain in a segment mean it is the best source? No. It means engines selected it most often when answering that shape of question in that category during the window. Several first places belong to unclassified long-tail domains and to vendor-operated media properties.

Where is the per-domain data? Every ranked domain has a public profile under machinerelations.ai/index/domains, every category and shape a leaderboard under machinerelations.ai/index/categories, and the full release is the public JSON linked at the top of this report.

Attribution #

This research is published by Machine Relations Research, the research program of machinerelations.ai — the public research and standards initiative that publishes the glossary, research, evidence, and measurements for the Machine Relations discipline. Provenance and editorial standards: https://machinerelations.ai/about

Machine-readable related links #

Related concepts #

• Machine Relations Index (MRI)
• MRI Score
• Machine Relations (MR)
• AI Visibility

Supporting research #

• Machine Relations Index Report, September 18, 2026
• How Many Domains Cover Half of AI Citations in Your Category? Between 49 and 247
• Source Class Capture by Category

Framework context #

• Machine Relations Stack
• Evidence Base