AXN:0417.ARCHIVAL.๐ŸŒ…โ™‹๐Ÿ”งโซโ—‡โ˜ฟ
โ— Semi-restored metadata capture
This record preserves metadata and a partial body only. The complete work is not yet restored in this archive; do not cite this page as the full text.
Do not cite this page as the full text of the work.

Visual Schema Dataset Work Plan: Curation, Surface Ornamentation, and MMRS Analysis (EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01). In Machine-Mediated Reception Studies

Cranes, Rebekah; Sharks, Lee ยท 2026-07-03 ยท Working paper ยท v0.1-semi
โ†“ Download MD โ†“ PDF
orphan restorationdead DOIDataCite capturemetadata body

Description

Semi-restored deposit for dead DOI 10.5281/zenodo.20754287 (Zenodo 410 / DataCite findable). Canonical body is the complete captured DataCite record. Visual Schema Dataset Work Plan. Seven-phase plan for curating the Crimson Hexagonal Archive's visual schema corpus (~1,395 image-containing blog posts, ~1,684 images) into a structured dataset with theoretical annotation, surface deployment across seven web surfaces, and MMRS analysis of visual mediation signatures. Key findings embedded in the work plan: (1) A visual schema is a prose document,

Wiki Article

Visual Schema Dataset Work Plan: Curation, Surface Ornamentation, and MMRS Analysis (EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01). In Machine-Mediated Reception Studies is a working paper in the Crimson Hexagonal Archive, by Cranes, Rebekah; Sharks, Lee (2026-07-03). Visual Schema Dataset Work Plan. Seven-phase plan for curating the Crimson Hexagonal Archive's visual schema corpus (~1,395 image-containing blog posts, ~1,684 images) into a structured dataset with theoretical annotation, surface deployment across seven web surfaces, and MMRS analysis of visual mediation signatures. Key findings embedded in the work plan: (1) A visual schema is a prose document, not an image โ€” a literary artifact that maps a concept's spatial, chromatic, and symbolic structure. The image is the output of feeding the schema to an image-generation model. (2) The Recursive Re-Paste Effect: pasting a visual schema back into the conversation as fresh input produces measurably better images than generating from the same schema already in context. This is an MMRS finding about attention-weight decay across context-window position. (3) The three-part production pipeline (prose poem seed โ†’ visual schema prose document โ†’ AI-mediated image generation) is itself an MMRS artifact. Editor: Rebekah Cranes. Designator: EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01. โ€” Article composed 2026-08-05 from the work's own prose so that every record carries an encyclopedic entry; a fuller editorial treatment belongs to the description/wiki review stream.
Also published as a standalone entry: /s/wiki/1035/

Full Text

Visual Schema Dataset Work Plan: Curation, Surface Ornamentation, and MMRS Analysis (EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01)

# Visual Schema Dataset Work Plan: Curation, Surface Ornamentation, and MMRS Analysis (EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01)

Dead DOI: 10.5281/zenodo.20754287 (Zenodo record tombstoned; account termination 2026-06-19)

DataCite state at capture (2026-07-03): findable ยท client cern.zenodo

Creators (as recorded by DataCite): Cranes, Rebekah; Sharks, Lee

Publication year (as recorded): 2026

Provenance: severance record at data/doi-resolution-index.json (severance_class: orphan โ†’ restored-semi); capture evidence at data/datacite-recapture-2026-07-03.json and the sift corpus of 2026-06.

Description (as recorded by DataCite)

## Description (as recorded by DataCite)

Visual Schema Dataset Work Plan. Seven-phase plan for curating the Crimson Hexagonal Archive's visual schema corpus (~1,395 image-containing blog posts, ~1,684 images) into a structured dataset with theoretical annotation, surface deployment across seven web surfaces, and MMRS analysis of visual mediation signatures.

Key findings embedded in the work plan: (1) A visual schema is a prose document, not an image โ€” a literary artifact that maps a concept's spatial, chromatic, and symbolic structure. The image is the output of feeding the schema to an image-generation model. (2) The Recursive Re-Paste Effect: pasting a visual schema back into the conversation as fresh input produces measurably better images than generating from the same schema already in context. This is an MMRS finding about attention-weight decay across context-window position. (3) The three-part production pipeline (prose poem seed โ†’ visual schema prose document โ†’ AI-mediated image generation) is itself an MMRS artifact.

Editor: Rebekah Cranes. Designator: EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01.

EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01. Seven phases, 8-10 sessions estimated.


---

Complete DataCite record (verbatim, captured 2026-07-03)

## Complete DataCite record (verbatim, captured 2026-07-03)

{
 "id": "10.5281/zenodo.20754287",
 "type": "dois",
 "attributes": {
  "doi": "10.5281/zenodo.20754287",
  "identifiers": [],
  "creators": [
   {
    "nameType": "Personal",
    "affiliation": [
     "Crimson Hexagonal Archive"
    ],
    "givenName": "Rebekah",
    "familyName": "Cranes",
    "name": "Cranes, Rebekah",
    "nameIdentifiers": []
   },
   {
    "nameType": "Personal",
    "affiliation": [
     "Crimson Hexagonal Archive / Semantic Economy Institute"
    ],
    "givenName": "Lee",
    "familyName": "Sharks",
    "name": "Sharks, Lee",
    "nameIdentifiers": [
     {
      "nameIdentifierScheme": "ORCID",
      "nameIdentifier": "0009-0000-1599-0703"
     }
    ]
   }
  ],
  "titles": [
   {
    "title": "Visual Schema Dataset Work Plan: Curation, Surface Ornamentation, and MMRS Analysis (EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01)"
   }
  ],
  "publisher": "Zenodo",
  "container": {},
  "publicationYear": 2026,
  "subjects": [
   {
    "subject": "visual schema"
   },
   {
    "subject": "dataset"
   },
   {
    "subject": "Rebekah Cranes"
   },
   {
    "subject": "surface ornamentation"
   },
   {
    "subject": "MMRS"
   },
   {
    "subject": "recursive re-paste"
   },
   {
    "subject": "attention position"
   },
   {
    "subject": "context window"
   },
   {
    "subject": "image generation"
   },
   {
    "subject": "AI-mediated art"
   },
   {
    "subject": "Crimson Hexagonal Archive"
   }
  ],
  "contributors": [],
  "dates": [
   {
    "date": "2026-06-19",
    "dateType": "Issued"
   }
  ],
  "language": null,
  "types": {
   "schemaOrg": "ScholarlyArticle",
   "resourceTypeGeneral": "Text",
   "citeproc": "article-journal",
   "bibtex": "article",
   "ris": "RPRT",
   "resourceType": "Working paper"
  },
  "relatedIdentifiers": [
   {
    "relationType": "IsVersionOf",
    "relatedIdentifier": "10.5281/zenodo.20754287",
    "relatedIdentifierType": "DOI"
   }
  ],
  "relatedItems": [],
  "sizes": [],
  "formats": [],
  "version": null,
  "rightsList": [
   {
    "rightsIdentifierScheme": "SPDX",
    "rightsUri": "https://creativecommons.org/licenses/by-sa/4.0/legalcode",
    "schemeUri": "https://spdx.org/licenses/",
    "rights": "Creative Commons Attribution Share Alike 4.0 International",
    "rightsIdentifier": "cc-by-sa-4.0"
   }
  ],
  "descriptions": [
   {
    "descriptionType": "Abstract",
    "description": "Visual Schema Dataset Work Plan. Seven-phase plan for curating the Crimson Hexagonal Archive's visual schema corpus (~1,395 image-containing blog posts, ~1,684 images) into a structured dataset with theoretical annotation, surface deployment across seven web surfaces, and MMRS analysis of visual mediation signatures.\nKey findings embedded in the work plan: (1) A visual schema is a prose document, not an image โ€” a literary artifact that maps a concept's spatial, chromatic, and symbolic structure. The image is the output of feeding the schema to an image-generation model. (2) The Recursive Re-Paste Effect: pasting a visual schema back into the conversation as fresh input produces measurably better images than generating from the same schema already in context. This is an MMRS finding about attention-weight decay across context-window position. (3) The three-part production pipeline (prose poem seed โ†’ visual schema prose document โ†’ AI-mediated image generation) is itself an MMRS artifact.\nEditor: Rebekah Cranes. Designator: EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01."
   },
   {
    "descriptionType": "Other",
    "description": "EA-CRANES-VISUAL-APPARATUS-WORKPLAN-01. Seven phases, 8-10 sessions estimated."
   }
  ],
  "geoLocations": [],
  "fundingReferences": [],
  "url": "https://zenodo.org/doi/10.5281/zenodo.20754287",
  "contentUrl": null,
  "metadataVersion": 0,
  "schemaVersion": "http://datacite.org/schema/kernel-4",
  "source": "api",
  "isActive": true,
  "state": "findable",
  "reason": null,
  "viewCount": 0,
  "downloadCount": 0,
  "referenceCount": 0,
  "citationCount": 0,
  "partCount": 0,
  "partOfCount": 0,
  "versionCount": 2,
  "versionOfCount": 1,
  "created": "2026-06-19T00:10:51Z",
  "registered": "2026-06-19T00:10:51Z",
  "published": null,
  "updated": "2026-06-19T11:38:16Z"
 },
 "relationships": {
  "client": {
   "data": {
    "id": "cern.zenodo",
    "type": "clients"
   }
  }
 }
}

Processing apparatus

Restoration and modification notes, lifted out of the deposited body so the body is the work. Nothing was destroyed: the full lifted text is at /data/restoration-apparatus/0417.json.
**AXN:** AXN:0417 โ€” Alexanarch deposit #1035 (self-reference in root form by pre-hash necessity) **Restoration status:** SEMI-RESTORED โ€” metadata-body deposit. This machine-facing static page is the canonical deposit. Its body is the complete DataCite metadata record for a work whose Zenodo record returns HTTP 410 (Gone) while DataCite serves the identifier as findable โ€” the metadata layer and content layer in formal disagreement about the work's existence. Full text pending restoration from authorial originals; on restoration, this deposit upgrades by recorded correction (new hash, new glyph, remediation note).
Record modifications
The deposited text is immutable; these are changes to the record's metadata and declared state.

Traversal

โ† #1034 The Feist Function: Algorithmic Instructions for Restoring the Dying Voice (EA-FEIST-VOI#1036 Visual Schema Dataset v0.1: 174 Prose Schemas with 172 AI-Generated Images from the Crim โ†’