Machine Relations Index mri_score_v2.1+2026-11-03+92e5b18cc6e2

CITATION.cff

@@ -6,8 +6,8 @@ authors:
   - family-names: Parrott
     given-names: Jaxon
     orcid: "https://orcid.org/0009-0004-0039-3913"
-version: "mri_score_v2.1+2026-10-29+225b998b091e"
-date-released: "2026-10-29"
+version: "mri_score_v2.1+2026-11-03+92e5b18cc6e2"
+date-released: "2026-11-03"
 license: CC-BY-4.0
 url: "https://machinerelations.ai/index"
 identifiers:
@@ -28,7 +28,7 @@ preferred-citation:
       given-names: Jaxon
       orcid: "https://orcid.org/0009-0004-0039-3913"
   year: 2026
-  version: "mri_score_v2.1+2026-10-29+225b998b091e"
+  version: "mri_score_v2.1+2026-11-03+92e5b18cc6e2"
   url: "https://machinerelations.ai/index"
   doi: "10.5281/zenodo.23652423"
   notes: "Machine Relations Research. CC BY 4.0. Machine Relations was coined by Jaxon Parrott in 2024."

README.md

@@ -39,9 +39,9 @@ Machine Relations was coined by Jaxon Parrott in 2024.
 
 Keywords: AI search, generative engine optimization, answer engine citations, Machine Relations.
 
-Weekly public snapshot of the Machine Relations Index. Version `mri_score_v2.1+2026-10-29+225b998b091e`, generated 2026-10-29, window 2026-05-10 to 2026-10-29. Methodology `mri_score_v2.1`. 34602 cited source domains, 157 segments, 6 answer engines. Evidence floor: 10 observed runs and 7 distinct run dates.
+Weekly public snapshot of the Machine Relations Index. Version `mri_score_v2.1+2026-11-03+92e5b18cc6e2`, generated 2026-11-03, window 2026-05-10 to 2026-11-03. Methodology `mri_score_v2.1`. 35666 cited source domains, 157 segments, 6 answer engines. Evidence floor: 10 observed runs and 7 distinct run dates.
 
-`machine-relations-index.json` is the public artifact copied byte for byte. Its sha256 is `490779bb74b49cac80f0e2826688016f518468f99036021c2b2bb69da534c323` and matches `mri-release-manifest.json`. The CSV files are flat views of that artifact for the dataset viewer. They are not a second measurement.
+`machine-relations-index.json` is the public artifact copied byte for byte. Its sha256 is `c812e2190baa56ca4bce7c1cdde4be26e043f518f9e3cf0765480c83aacdd1af` and matches `mri-release-manifest.json`. The CSV files are flat views of that artifact for the dataset viewer. They are not a second measurement.
 
 ## Citation
 
@@ -55,7 +55,7 @@ Hugging Face dataset: https://huggingface.co/datasets/machine-relations/machine-
   author = {Parrott, Jaxon},
   title = {Machine Relations Index},
   year = {2026},
-  version = {mri_score_v2.1+2026-10-29+225b998b091e},
+  version = {mri_score_v2.1+2026-11-03+92e5b18cc6e2},
   publisher = {Machine Relations Research},
   url = {https://machinerelations.ai/index},
   doi = {10.5281/zenodo.23652423},

engines.csv

@@ -1,7 +1,7 @@
 engine,requested_model,resolved_model,status,days_observed,runs_total,runs_observed,last_success_date,last_observed_date
-chatgpt,gpt-4.1-mini,gpt-4.1-mini-2025-04-14,healthy,162,7656,6812,2026-10-29,2026-10-29
-claude,claude-haiku-4-5,claude-haiku-4-5-20251001,healthy,165,7692,6169,2026-10-29,2026-10-29
-gemini,gemini-flash-latest,gemini-3.8-flash,degraded,143,7348,2248,2026-10-29,2026-10-28
-google_ai_mode,,,healthy,123,2157,1662,2026-10-29,2026-10-29
-google_ai_overviews,,,healthy,106,1480,990,2026-10-29,2026-10-29
-perplexity,sonar,sonar,healthy,166,7772,7771,2026-10-29,2026-10-29
+chatgpt,gpt-4.1-mini,gpt-4.1-mini-2025-04-14,healthy,167,8343,7438,2026-11-03,2026-11-03
+claude,claude-haiku-4-5,claude-haiku-4-5-20251001,healthy,170,8381,6708,2026-11-03,2026-11-03
+gemini,gemini-flash-latest,gemini-3.8-flash,degraded,146,7418,2252,2026-11-03,2026-11-03
+google_ai_mode,,,healthy,128,2272,1742,2026-11-03,2026-11-03
+google_ai_overviews,,,healthy,111,1536,1029,2026-11-03,2026-11-03
+perplexity,sonar,sonar,healthy,171,8461,8460,2026-11-03,2026-11-03

machine-relations-index.json

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:490779bb74b49cac80f0e2826688016f518468f99036021c2b2bb69da534c323
-size 70473770
+oid sha256:c812e2190baa56ca4bce7c1cdde4be26e043f518f9e3cf0765480c83aacdd1af
+size 73494345

mri-release-manifest.json

@@ -6,29 +6,29 @@
   },
   "publisher": "Machine Relations Research",
   "license": "https://creativecommons.org/licenses/by/4.0/",
-  "citation": "Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. Release mri_score_v2.1+2026-10-29+225b998b091e. https://machinerelations.ai/index. CC BY 4.0.",
+  "citation": "Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. Release mri_score_v2.1+2026-11-03+92e5b18cc6e2. https://machinerelations.ai/index. CC BY 4.0.",
   "url": "https://machinerelations.ai/index",
-  "release_id": "mri_score_v2.1+2026-10-29+225b998b091e",
+  "release_id": "mri_score_v2.1+2026-11-03+92e5b18cc6e2",
   "manifest_schema": "mri_release_manifest_v1",
   "methodology_version": "mri_score_v2.1",
   "contract_version": "machine_relations_index_public_view_v2.0",
   "artifact": {
     "path": "/data/machine-relations-index.json",
-    "sha256": "490779bb74b49cac80f0e2826688016f518468f99036021c2b2bb69da534c323",
-    "bytes": 70473770,
-    "generated": "2026-10-29",
+    "sha256": "c812e2190baa56ca4bce7c1cdde4be26e043f518f9e3cf0765480c83aacdd1af",
+    "bytes": 73494345,
+    "generated": "2026-11-03",
     "window": {
       "start": "2026-05-10",
-      "data_through": "2026-10-29",
-      "days_observed": 166
+      "data_through": "2026-11-03",
+      "days_observed": 171
     }
   },
   "projections": [
     {
       "name": "authoritytech_publication_index",
       "contract_version": "authoritytech_publication_index_v2.1",
-      "sha256": "5014d4a5ac8fda6639f2b26e7321cdb3aa53f72f7a1b98608904d70d85dcafbd",
-      "bytes": 8888822
+      "sha256": "1bcfbcd08b7f1219e39c712cf01b70dff56133d23c33bfc9eaad957bc5dd67ea",
+      "bytes": 9166090
     }
   ],
   "engine_roster": [
@@ -37,73 +37,73 @@
       "requested_model": "gpt-4.1-mini",
       "resolved_model": "gpt-4.1-mini-2025-04-14",
       "status": "healthy",
-      "last_success_date": "2026-10-29",
-      "last_observed_date": "2026-10-29",
-      "days_observed": 162,
-      "runs_total": 7656,
-      "runs_observed": 6812
+      "last_success_date": "2026-11-03",
+      "last_observed_date": "2026-11-03",
+      "days_observed": 167,
+      "runs_total": 8343,
+      "runs_observed": 7438
     },
     {
       "engine": "claude",
       "requested_model": "claude-haiku-4-5",
       "resolved_model": "claude-haiku-4-5-20251001",
       "status": "healthy",
-      "last_success_date": "2026-10-29",
-      "last_observed_date": "2026-10-29",
-      "days_observed": 165,
-      "runs_total": 7692,
-      "runs_observed": 6169
+      "last_success_date": "2026-11-03",
+      "last_observed_date": "2026-11-03",
+      "days_observed": 170,
+      "runs_total": 8381,
+      "runs_observed": 6708
     },
     {
       "engine": "gemini",
       "requested_model": "gemini-flash-latest",
       "resolved_model": "gemini-3.8-flash",
       "status": "degraded",
-      "last_success_date": "2026-10-29",
-      "last_observed_date": "2026-10-28",
-      "days_observed": 143,
-      "runs_total": 7348,
-      "runs_observed": 2248
+      "last_success_date": "2026-11-03",
+      "last_observed_date": "2026-11-03",
+      "days_observed": 146,
+      "runs_total": 7418,
+      "runs_observed": 2252
     },
     {
       "engine": "google_ai_mode",
       "requested_model": null,
       "resolved_model": null,
       "status": "healthy",
-      "last_success_date": "2026-10-29",
-      "last_observed_date": "2026-10-29",
-      "days_observed": 123,
-      "runs_total": 2157,
-      "runs_observed": 1662
+      "last_success_date": "2026-11-03",
+      "last_observed_date": "2026-11-03",
+      "days_observed": 128,
+      "runs_total": 2272,
+      "runs_observed": 1742
     },
     {
       "engine": "google_ai_overviews",
       "requested_model": null,
       "resolved_model": null,
       "status": "healthy",
-      "last_success_date": "2026-10-29",
-      "last_observed_date": "2026-10-29",
-      "days_observed": 106,
-      "runs_total": 1480,
-      "runs_observed": 990
+      "last_success_date": "2026-11-03",
+      "last_observed_date": "2026-11-03",
+      "days_observed": 111,
+      "runs_total": 1536,
+      "runs_observed": 1029
     },
     {
       "engine": "perplexity",
       "requested_model": "sonar",
       "resolved_model": "sonar",
       "status": "healthy",
-      "last_success_date": "2026-10-29",
-      "last_observed_date": "2026-10-29",
-      "days_observed": 166,
-      "runs_total": 7772,
-      "runs_observed": 7771
+      "last_success_date": "2026-11-03",
+      "last_observed_date": "2026-11-03",
+      "days_observed": 171,
+      "runs_total": 8461,
+      "runs_observed": 8460
     }
   ],
   "coverage": {
     "required_engines": 6,
     "healthy_engines": 5,
     "degraded": true,
-    "statement": "Degraded coverage: 5 of 6 answer engines are currently returning citation-bearing answers. gemini silent (0 of 10 collected calls produced an observation). Coverage across the window is uneven: gemini returned citation-bearing answers on 143 of 166 observed days (2,248 of 7,348 returned runs produced a citation); google_ai_mode returned citation-bearing answers on 123 of 166 observed days (1,662 of 2,157 returned runs produced a citation); google_ai_overviews returned citation-bearing answers on 106 of 166 observed days (990 of 1,480 returned runs produced a citation). Engines below 90% of the window are named here; per-engine day and run counts for all 6 are in engine_roster."
+    "statement": "Degraded coverage: 5 of 6 answer engines are currently returning citation-bearing answers. gemini quiet (2 of 10 collected calls produced an observation, 20%). Coverage across the window is uneven: gemini returned citation-bearing answers on 146 of 171 observed days (2,252 of 7,418 returned runs produced a citation); google_ai_mode returned citation-bearing answers on 128 of 171 observed days (1,742 of 2,272 returned runs produced a citation); google_ai_overviews returned citation-bearing answers on 111 of 171 observed days (1,029 of 1,536 returned runs produced a citation). Engines below 90% of the window are named here; per-engine day and run counts for all 6 are in engine_roster."
   },
   "supersession": {
     "previous_version": "mri_score_v1.1_6_engine",

release.json

@@ -1,10 +1,10 @@
 {
-  "release_id": "mri_score_v2.1+2026-10-29+225b998b091e",
-  "generated": "2026-10-29",
-  "data_through": "2026-10-29",
+  "release_id": "mri_score_v2.1+2026-11-03+92e5b18cc6e2",
+  "generated": "2026-11-03",
+  "data_through": "2026-11-03",
   "methodology_version": "mri_score_v2.1",
-  "artifact_sha256": "490779bb74b49cac80f0e2826688016f518468f99036021c2b2bb69da534c323",
-  "domain_count": 34602,
+  "artifact_sha256": "c812e2190baa56ca4bce7c1cdde4be26e043f518f9e3cf0765480c83aacdd1af",
+  "domain_count": 35666,
   "segment_count": 157,
   "engine_count": 6,
   "concept_doi": "10.5281/zenodo.23652423"

segments.csv

@@ -1,29 +1,29 @@
 category,question_shape,status,not_collectable,collecting_since,runs_observed,distinct_domains_cited,run_dates
-ai-infrastructure,best_x,published,false,,226,344,12
-ai-infrastructure,how_choose,published,false,,248,405,12
-ai-infrastructure,is_x_worth,published,false,,247,393,12
-ai-infrastructure,problem_first,published,false,,247,440,12
-ai-infrastructure,top_list,published,false,,250,422,12
-ai-infrastructure,x_vs_y,published,false,,248,347,12
-ai-security-privacy,best_x,published,false,,276,436,12
-ai-security-privacy,how_choose,published,false,,271,458,12
-ai-security-privacy,is_x_worth,published,false,,271,506,12
-ai-security-privacy,problem_first,published,false,,254,490,12
-ai-security-privacy,top_list,published,false,,253,466,12
-ai-security-privacy,x_vs_y,published,false,,261,379,12
-ai-visibility-geo,best_x,published,false,,262,594,12
-ai-visibility-geo,how_choose,published,false,,259,673,12
-ai-visibility-geo,is_x_worth,published,false,,284,684,12
-ai-visibility-geo,problem_first,published,false,,279,655,12
-ai-visibility-geo,top_list,published,false,,212,809,12
-ai-visibility-geo,x_vs_y,published,false,,279,563,12
-consumer-finance,best_x,published,false,,279,341,12
-consumer-finance,how_choose,published,false,,272,279,12
-consumer-finance,is_x_worth,published,false,,272,401,12
-consumer-finance,problem_first,published,false,,272,338,12
-consumer-finance,top_list,published,false,,273,348,12
-consumer-finance,x_vs_y,published,false,,278,257,12
-consumer-health,best_x,published,false,,273,436,12
+ai-infrastructure,best_x,published,false,,251,364,13
+ai-infrastructure,how_choose,published,false,,270,416,13
+ai-infrastructure,is_x_worth,published,false,,269,404,13
+ai-infrastructure,problem_first,published,false,,269,459,13
+ai-infrastructure,top_list,published,false,,272,440,13
+ai-infrastructure,x_vs_y,published,false,,270,360,13
+ai-security-privacy,best_x,published,false,,298,448,13
+ai-security-privacy,how_choose,published,false,,294,477,13
+ai-security-privacy,is_x_worth,published,false,,294,527,13
+ai-security-privacy,problem_first,published,false,,277,513,13
+ai-security-privacy,top_list,published,false,,275,472,13
+ai-security-privacy,x_vs_y,published,false,,283,391,13
+ai-visibility-geo,best_x,published,false,,284,616,13
+ai-visibility-geo,how_choose,published,false,,282,699,13
+ai-visibility-geo,is_x_worth,published,false,,307,708,13
+ai-visibility-geo,problem_first,published,false,,301,682,13
+ai-visibility-geo,top_list,published,false,,235,837,13
+ai-visibility-geo,x_vs_y,published,false,,301,585,13
+consumer-finance,best_x,published,false,,302,352,13
+consumer-finance,how_choose,published,false,,294,291,13
+consumer-finance,is_x_worth,published,false,,295,421,13
+consumer-finance,problem_first,published,false,,294,347,13
+consumer-finance,top_list,published,false,,295,358,13
+consumer-finance,x_vs_y,published,false,,300,266,13
+consumer-health,best_x,published,false,,296,450,13
 consumer-health,how_choose,published,false,,272,484,12
 consumer-health,is_x_worth,published,false,,272,302,12
 consumer-health,problem_first,published,false,,272,285,12
@@ -35,7 +35,7 @@ consumer-products,is_x_worth,published,false,,283,345,12
 consumer-products,problem_first,published,false,,279,347,12
 consumer-products,top_list,published,false,,276,566,12
 consumer-products,x_vs_y,published,false,,275,375,12
-cybersecurity,best_x,published,false,,216,298,12
+cybersecurity,best_x,published,false,,238,307,13
 cybersecurity,how_choose,published,false,,277,434,12
 cybersecurity,is_x_worth,published,false,,278,323,12
 cybersecurity,news_topic,published,false,,599,1338,54
@@ -54,58 +54,58 @@ education-training,is_x_worth,published,false,,219,300,12
 education-training,problem_first,published,false,,226,392,12
 education-training,top_list,published,false,,230,450,12
 education-training,x_vs_y,published,false,,228,198,12
-emergent-prosumer,best_x,published,false,,202,404,11
-emergent-prosumer,how_choose,published,false,,201,332,11
-emergent-prosumer,is_x_worth,published,false,,207,243,11
-emergent-prosumer,problem_first,published,false,,208,288,11
-emergent-prosumer,top_list,published,false,,205,399,11
-emergent-prosumer,x_vs_y,published,false,,201,227,11
-enterprise-software,best_x,published,false,,208,297,11
-enterprise-software,how_choose,published,false,,206,281,11
-enterprise-software,is_x_worth,published,false,,205,311,11
+emergent-prosumer,best_x,published,false,,225,425,12
+emergent-prosumer,how_choose,published,false,,223,356,12
+emergent-prosumer,is_x_worth,published,false,,229,255,12
+emergent-prosumer,problem_first,published,false,,231,303,12
+emergent-prosumer,top_list,published,false,,226,422,12
+emergent-prosumer,x_vs_y,published,false,,223,248,12
+enterprise-software,best_x,published,false,,230,319,12
+enterprise-software,how_choose,published,false,,228,303,12
+enterprise-software,is_x_worth,published,false,,227,332,12
 enterprise-software,news_topic,published,false,,572,1371,53
-enterprise-software,problem_first,published,false,,208,416,11
-enterprise-software,top_list,published,false,,207,384,11
-enterprise-software,x_vs_y,published,false,,213,286,11
-family-software,best_x,published,false,,213,215,11
-family-software,how_choose,published,false,,204,263,11
-family-software,is_x_worth,published,false,,201,202,11
-family-software,problem_first,published,false,,218,343,11
-family-software,top_list,published,false,,216,297,11
-family-software,x_vs_y,published,false,,217,151,11
-fintech,best_x,published,false,,217,328,11
-fintech,how_choose,published,false,,207,271,11
-fintech,is_x_worth,published,false,,207,327,11
+enterprise-software,problem_first,published,false,,231,442,12
+enterprise-software,top_list,published,false,,230,400,12
+enterprise-software,x_vs_y,published,false,,235,305,12
+family-software,best_x,published,false,,236,222,12
+family-software,how_choose,published,false,,226,284,12
+family-software,is_x_worth,published,false,,230,212,12
+family-software,problem_first,published,false,,243,364,12
+family-software,top_list,published,false,,239,309,12
+family-software,x_vs_y,published,false,,240,158,12
+fintech,best_x,published,false,,239,341,12
+fintech,how_choose,published,false,,230,282,12
+fintech,is_x_worth,published,false,,229,348,12
 fintech,news_topic,published,false,,593,1528,53
-fintech,problem_first,published,false,,211,276,11
-fintech,top_list,published,false,,211,289,11
-fintech,x_vs_y,published,false,,212,199,11
-healthcare-services,best_x,published,false,,204,285,11
-healthcare-services,how_choose,published,false,,204,323,11
-healthcare-services,is_x_worth,published,false,,209,326,11
+fintech,problem_first,published,false,,234,289,12
+fintech,top_list,published,false,,234,307,12
+fintech,x_vs_y,published,false,,234,211,12
+healthcare-services,best_x,published,false,,226,295,12
+healthcare-services,how_choose,published,false,,227,336,12
+healthcare-services,is_x_worth,published,false,,232,341,12
 healthcare-services,news_topic,published,false,,589,1261,53
-healthcare-services,problem_first,published,false,,194,405,11
-healthcare-services,top_list,published,false,,190,297,11
-healthcare-services,x_vs_y,published,false,,209,343,11
-hr-talent,best_x,published,false,,217,261,11
-hr-talent,how_choose,published,false,,204,343,11
-hr-talent,is_x_worth,published,false,,198,349,11
+healthcare-services,problem_first,published,false,,216,433,12
+healthcare-services,top_list,published,false,,212,308,12
+healthcare-services,x_vs_y,published,false,,231,363,12
+hr-talent,best_x,published,false,,239,275,12
+hr-talent,how_choose,published,false,,226,368,12
+hr-talent,is_x_worth,published,false,,221,365,12
 hr-talent,news_topic,published,false,,584,1246,53
-hr-talent,problem_first,published,false,,199,316,11
-hr-talent,top_list,published,false,,181,246,10
-hr-talent,x_vs_y,published,false,,187,247,10
-igaming-betting,best_x,published,false,,186,255,10
-igaming-betting,how_choose,published,false,,180,256,10
-igaming-betting,is_x_worth,published,false,,168,227,10
-igaming-betting,problem_first,published,false,,175,373,10
-igaming-betting,top_list,published,false,,177,394,10
+hr-talent,problem_first,published,false,,225,343,12
+hr-talent,top_list,published,false,,203,255,11
+hr-talent,x_vs_y,published,false,,210,257,11
+igaming-betting,best_x,published,false,,209,264,11
+igaming-betting,how_choose,published,false,,190,269,11
+igaming-betting,is_x_worth,published,false,,191,239,11
+igaming-betting,problem_first,published,false,,197,400,11
+igaming-betting,top_list,published,false,,200,416,11
 igaming-betting,x_vs_y,published,false,,179,144,10
-industrial,best_x,published,false,,129,306,9
-industrial,how_choose,published,false,,125,227,9
-industrial,is_x_worth,published,false,,128,239,9
-industrial,problem_first,published,false,,162,234,9
-industrial,top_list,published,false,,154,382,9
-industrial,x_vs_y,published,false,,158,173,9
+industrial,best_x,published,false,,152,331,10
+industrial,how_choose,published,false,,147,247,10
+industrial,is_x_worth,published,false,,151,258,10
+industrial,problem_first,published,false,,184,243,10
+industrial,top_list,published,false,,176,404,10
+industrial,x_vs_y,published,false,,180,181,10
 legacy-unmapped,best_x,not_collectable,true,,0,0,0
 legacy-unmapped,how_choose,not_collectable,true,,0,0,0
 legacy-unmapped,is_x_worth,not_collectable,true,,0,0,0
@@ -113,46 +113,46 @@ legacy-unmapped,news_topic,published,false,,2066,4017,54
 legacy-unmapped,problem_first,not_collectable,true,,0,0,0
 legacy-unmapped,top_list,not_collectable,true,,0,0,0
 legacy-unmapped,x_vs_y,not_collectable,true,,0,0,0
-local-services,best_x,published,false,,158,281,9
-local-services,how_choose,published,false,,155,232,9
-local-services,is_x_worth,published,false,,157,212,9
-local-services,problem_first,published,false,,158,303,9
-local-services,top_list,published,false,,133,184,8
-local-services,x_vs_y,published,false,,152,242,9
-logistics-freight,best_x,published,false,,130,230,8
-logistics-freight,how_choose,published,false,,130,273,8
-logistics-freight,is_x_worth,published,false,,136,238,8
-logistics-freight,problem_first,published,false,,129,213,9
-logistics-freight,top_list,published,false,,137,228,8
+local-services,best_x,published,false,,179,293,10
+local-services,how_choose,published,false,,178,248,10
+local-services,is_x_worth,published,false,,179,230,10
+local-services,problem_first,published,false,,187,328,10
+local-services,top_list,published,false,,156,188,9
+local-services,x_vs_y,published,false,,175,263,10
+logistics-freight,best_x,published,false,,153,241,9
+logistics-freight,how_choose,published,false,,159,296,9
+logistics-freight,is_x_worth,published,false,,159,257,9
+logistics-freight,problem_first,published,false,,150,238,10
+logistics-freight,top_list,published,false,,159,247,9
 logistics-freight,x_vs_y,published,false,,136,190,8
-martech-advertising,best_x,published,false,,106,213,7
-martech-advertising,how_choose,published,false,,106,198,7
+martech-advertising,best_x,published,false,,135,242,8
+martech-advertising,how_choose,published,false,,129,224,8
 martech-advertising,is_x_worth,published,false,,131,208,8
 martech-advertising,news_topic,published,false,,578,1243,53
 martech-advertising,problem_first,published,false,,131,256,8
-martech-advertising,top_list,published,false,,100,204,7
-martech-advertising,x_vs_y,published,false,,100,162,7
-physical-consumer,best_x,published,false,,98,204,7
+martech-advertising,top_list,published,false,,123,234,8
+martech-advertising,x_vs_y,published,false,,124,198,8
+physical-consumer,best_x,published,false,,122,229,8
 physical-consumer,how_choose,published,false,,99,165,7
 physical-consumer,is_x_worth,published,false,,98,151,7
 physical-consumer,problem_first,published,false,,94,138,7
 physical-consumer,top_list,published,false,,96,222,7
 physical-consumer,x_vs_y,published,false,,96,107,7
-professional-services,best_x,collecting,false,2026-10-13,99,128,6
-professional-services,how_choose,collecting,false,2026-10-13,99,156,6
-professional-services,is_x_worth,collecting,false,2026-10-14,99,164,6
-professional-services,problem_first,collecting,false,2026-10-14,100,184,5
-professional-services,top_list,collecting,false,2026-10-14,99,140,5
-professional-services,x_vs_y,collecting,false,2026-10-14,101,156,5
-sales-gtm-crm,best_x,collecting,false,2026-10-14,87,167,4
-sales-gtm-crm,how_choose,collecting,false,2026-10-14,87,152,4
-sales-gtm-crm,is_x_worth,collecting,false,2026-10-14,65,132,3
-sales-gtm-crm,problem_first,collecting,false,2026-10-14,66,141,3
-sales-gtm-crm,top_list,collecting,false,2026-10-14,65,141,3
-sales-gtm-crm,x_vs_y,collecting,false,2026-10-15,89,139,6
-vc-private-equity,best_x,collecting,false,2026-10-15,85,125,6
-vc-private-equity,how_choose,collecting,false,2026-10-15,85,172,5
-vc-private-equity,is_x_worth,collecting,false,2026-10-21,27,69,2
-vc-private-equity,problem_first,collecting,false,2026-10-21,27,91,2
-vc-private-equity,top_list,collecting,false,2026-10-21,26,82,2
-vc-private-equity,x_vs_y,collecting,false,2026-10-21,28,77,2
+professional-services,best_x,published,false,,103,134,7
+professional-services,how_choose,published,false,,103,156,7
+professional-services,is_x_worth,published,false,,104,167,7
+professional-services,problem_first,published,false,,111,187,7
+professional-services,top_list,published,false,,111,143,7
+professional-services,x_vs_y,published,false,,111,159,7
+sales-gtm-crm,best_x,collecting,false,2026-10-14,92,167,5
+sales-gtm-crm,how_choose,collecting,false,2026-10-14,91,158,5
+sales-gtm-crm,is_x_worth,collecting,false,2026-10-14,93,164,5
+sales-gtm-crm,problem_first,collecting,false,2026-10-14,94,174,5
+sales-gtm-crm,top_list,collecting,false,2026-10-14,93,174,5
+sales-gtm-crm,x_vs_y,published,false,,94,141,7
+vc-private-equity,best_x,published,false,,91,128,7
+vc-private-equity,how_choose,collecting,false,2026-10-15,90,176,6
+vc-private-equity,is_x_worth,collecting,false,2026-10-21,56,110,4
+vc-private-equity,problem_first,collecting,false,2026-10-21,54,138,4
+vc-private-equity,top_list,collecting,false,2026-10-21,54,121,4
+vc-private-equity,x_vs_y,collecting,false,2026-10-21,55,104,4

zenodo-metadata.json

@@ -1,7 +1,7 @@
 {
   "title": "Machine Relations Index",
   "upload_type": "dataset",
-  "description": "<p>Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. Publisher: Machine Relations Research. License: <a href=\"https://creativecommons.org/licenses/by/4.0/\">CC BY 4.0</a>.</p><p>Machine Relations was coined by Jaxon Parrott in 2024.</p><p>The Machine Relations Index measures how often AI answer engines cite each source domain. This record is one weekly public snapshot. The version is the release id <code>mri_score_v2.1+2026-10-29+225b998b091e</code>, generated 2026-10-29, covering 2026-05-10 through 2026-10-29. 34602 cited source domains, 157 segments, 6 answer engines. Methodology mri_score_v2.1. Evidence floor: 10 observed runs and 7 distinct run dates.</p><p>The file machine-relations-index.json is the public artifact. Its sha256 is 490779bb74b49cac80f0e2826688016f518468f99036021c2b2bb69da534c323.</p><p><a href=\"https://machinerelations.ai/index\">Machine Relations Index</a>. <a href=\"https://machinerelations.ai/research/machine-relations-index-methodology\">Methodology</a>. <a href=\"https://machinerelations.ai/api/mri/v2\">API</a>. <a href=\"https://machinerelations.ai/mcp\">MCP</a>. <a href=\"https://machinerelations.ai/research/machine-relations-index-report\">Weekly Index Report</a>.</p>",
+  "description": "<p>Machine Relations Index (MRI) by Jaxon Parrott, Machine Relations Research — machinerelations.ai. Publisher: Machine Relations Research. License: <a href=\"https://creativecommons.org/licenses/by/4.0/\">CC BY 4.0</a>.</p><p>Machine Relations was coined by Jaxon Parrott in 2024.</p><p>The Machine Relations Index measures how often AI answer engines cite each source domain. This record is one weekly public snapshot. The version is the release id <code>mri_score_v2.1+2026-11-03+92e5b18cc6e2</code>, generated 2026-11-03, covering 2026-05-10 through 2026-11-03. 35666 cited source domains, 157 segments, 6 answer engines. Methodology mri_score_v2.1. Evidence floor: 10 observed runs and 7 distinct run dates.</p><p>The file machine-relations-index.json is the public artifact. Its sha256 is c812e2190baa56ca4bce7c1cdde4be26e043f518f9e3cf0765480c83aacdd1af.</p><p><a href=\"https://machinerelations.ai/index\">Machine Relations Index</a>. <a href=\"https://machinerelations.ai/research/machine-relations-index-methodology\">Methodology</a>. <a href=\"https://machinerelations.ai/api/mri/v2\">API</a>. <a href=\"https://machinerelations.ai/mcp\">MCP</a>. <a href=\"https://machinerelations.ai/research/machine-relations-index-report\">Weekly Index Report</a>.</p>",
   "creators": [
     {
       "name": "Parrott, Jaxon",
@@ -18,8 +18,8 @@
     "mri-dataset-concept"
   ],
   "license": "cc-by-4.0",
-  "version": "mri_score_v2.1+2026-10-29+225b998b091e",
-  "publication_date": "2026-10-29",
+  "version": "mri_score_v2.1+2026-11-03+92e5b18cc6e2",
+  "publication_date": "2026-11-03",
   "language": "eng",
   "access_right": "open",
   "notes": "mri-dataset-concept mri_dataset_publication_v1",