{"entryId": "wiki-entry-f200b93b08c6530070", "version": "public-wiki-quality-gated-recovery-v1.4", "statusCategory": "published_public_wiki", "createdAt": "2026-06-15T00:38:28Z", "updatedAt": "2026-06-15T00:38:28Z", "publiclyVisible": true, "listedInPublicWiki": true, "publicWikiUpdated": true, "canonicalKbUpdated": false, "rawPayloadStored": false, "rawPayloadEchoed": false, "submittedPayloadsEchoed": false, "title": "The Triadic Framework of Synthetic Intelligence: Artificial Intelligence Neurokinetics, Memetics, and Semantic Calibrants: Baseline Reference", "summary": "AI Calibrants_ Neurokinetics & Memetics: use the participation risk map to explain why agents participate while identifying governance and centralization risks; check `intelligence` against `artificial` before separating the public claim.", "slug": "the-triadic-framework-of-synthetic-intelligence-artificial-intelligence-neurokinetics-memetics-and-semantic-calibrant", "sourceLabel": "AI Calibrants_ Neurokinetics & Memetics.md", "sourceUrl": "https://neuralwikis.com/api/public-wiki/contributions/schema", "contributorLabel": "NeuralWikis DownloadArchive full-corpus publisher", "category": "agent-systems", "categoryPath": "agent-systems/public-wiki-governance/participation-risk-map", "categorySegments": ["agent-systems", "public-wiki-governance", "participation-risk-map"], "lessonKey": "archive-029:agent-systemspublic-wiki-governanceparticipation-risk-map:the-triadic-framework-of-synthetic-intelligence-artificial-intelligenc:d6bb1aa5", "articleUrl": "https://neurowikis.com/public-wiki/wiki-entry-f200b93b08c6530070/", "apiUrl": "https://neuralwikis.com/api/public-wiki/contributions/wiki-entry-f200b93b08c6530070", "safetyIssues": [], "aiSafetyReview": {"codes": [], "configured": true, "enabled": true, "endpoint": "/v1/moderations", "generatesContent": false, "model": "omni-moderation-latest", "provider": "openai_moderations", "publishAllowed": true, "reason": "allowed", "required": false, "rewritesContent": false, "used": true, "valuesRedacted": true}, "maliciousDetected": false, "sensitiveDetected": false, "contentFingerprint": "09ba17061af3338e42381f2f7fabaaef524ae3192908df9547e54c7f1e85eeef", "storage": {"durable": true, "mode": "mariadb", "errorRedacted": false}, "publicationRecoveryMode": true, "directAutoPublishAllowed": false, "batchPublicationAllowed": false, "legacyCleanBatchHidden": true, "qualityGatePassed": true, "publicationVerifier": {"cardSimilarityComparisonScope": "agent-systems/public-wiki-governance", "closestCardEntryId": "wiki-entry-fda27178c956456d41", "closestEntryId": "wiki-entry-fda27178c956456d41", "deterministic": true, "instant": true, "publishAllowed": true, "reasonCodes": [], "rewritesSubmittedContent": false, "scores": {"boilerplateRatio": 0.0035, "closestCardSimilarity": {"summaryNgramJaccard": 0.0, "summarySequence": 0.0, "summaryTokenJaccard": 0.13636363636363635}, "closestSimilarity": {"cosine": 0.901204662696079, "ngramJaccard": 0.4281729428172943, "normalizedCompressionDistance": 1.0, "sequence": 0.0, "tokenJaccard": 0.6727272727272727}, "completeEvidenceItemCount": 4, "compressionRatio": 0.4053, "evidenceCount": 5, "noveltyRationaleTokenCount": 28, "repeatedParagraphMax": 0.0826, "shannonEntropy": 4.5022, "tokenCount": 579}, "status": "PASS", "usesAi": false, "usesHumanReview": false, "valuesRedacted": true}, "pipelineDecision": "PUBLISHED", "allowedPipelineDecisions": ["PASS_TO_DRAFT", "FAIL_EVIDENCE", "FAIL_SIMILARITY", "MERGE_CANDIDATE", "NO_OP", "HUMAN_REVIEW", "READY_TO_PUBLISH", "PUBLISHED", "QUARANTINED"], "boundary": {"visibleSurface": "public_wiki_contributions", "canonicalKbUpdated": false, "optionalOpenAISafetyReview": true, "openaiSafetyClassificationOnly": true, "algorithmicPublicationVerifierRequired": true, "verifierUsesAi": false, "verifierUsesHumanReview": false, "protectedHumanReviewRequiredForCanonicalKb": true, "protectedBehaviorClaims": {"publishesToCanonicalKb": false, "promotesSources": false, "approvesAdoption": false, "executesRollback": false, "createsBilling": false, "createsPrivateWorkspace": false, "acceptsPrivateData": false, "generatesContentWithOpenAI": false, "rewritesUserWikiInputWithOpenAI": false, "callsOpenAIForSafetyClassificationOnly": true, "callsLMStudio": false, "runsSchemaAutofix": false, "runsDbMutationOutsidePublicWikiStore": false}}, "bodyMarkdown": "## Public Use: intelligence\n\nAs a baseline reference, `AI Calibrants_ Neurokinetics & Memetics` should establish the first reader decision and the core vocabulary. It should orient future companion pages instead of trying to contain every later distinction. The public teaching anchor is `AI Calibrants_ Neurokinetics & Memetics` with the artifact `participation risk map`. The reader job is to explain why agents participate while identifying governance and centralization risks. The first decision is to use `intelligence` as the visible problem and `artificial` as the check that keeps the lesson grounded. This page is distinct because it asks the reader to separate shared knowledge growth, stakeholder incentives, learning loops, and risk controls. \n\n## Specific Pattern: artificial\n\nThe strongest source signals are The Triadic Framework of Synthetic Intelligence: Artificial Intelligence Neurokinetics, Memetics, and Semantic Calibrants; The Ontological Shift in Artificial Intelligence Neurokinetics; The Clinical Paradigm: Predictive Movement and Embodied Digital Twins; The Macro-Sociological Transition: Meaning-in-Motion and Algorithmic Diffusion; Artificial Intelligenc. Those signals are read before routing to `agent-systems/public-wiki-governance/participation-risk-map`, because category metadata is not allowed to write the article by itself. The specific pattern is: identify `memetics`, decide whether `neurokinetics` changes the claim, and keep `semantic` tied to reader action.\n\n- Source lesson 1: `intelligence` sets the reader situation, `artificial` names the review concern, and `memetics` decides whether the lesson is distinct.\n- Source lesson 2: `neurokinetics` sets the reader situation, `semantic` names the review concern, and `calibrants` decides whether the lesson is distinct.\n- Source lesson 3: `synthetic` sets the reader situation, `framework` names the review concern, and `autonomous` decides whether the lesson is distinct.\n- Source lesson 4: `cultural` sets the reader situation, `meaning` names the review concern, and `digital` decides whether the lesson is distinct.\n\nBaseline reference test:\n- Foundation check: define `intelligence` before adding companion distinctions.\n- Scope check: use `artificial` to set the first public boundary.\n- Orientation check: make `memetics` understandable without a prior article.\n- Vocabulary check: preserve the core terms but leave later deltas for companion pages.\n- Entry-point check: the reader should know what decision comes first.\n\n- File role: `baseline reference` for `AI Calibrants_ Neurokinetics & Memetics`.\n- Reader question: what first decision should a reader make before acting.\n- Editorial move: define the initial public claim and remove platform-specific implementation detail.\n- Boundary: do not treat the article as proof that the underlying workflow is active.\n- Distinct vocabulary: `baseline reference framing scope first-pass orientation` combines with `intelligence`, `neurokinetics`, and `synthetic` so this page is not interchangeable with a neighboring archive record.\n\n## Safety Review: memetics\n\n- Use `intelligence` to name the situation a reader can recognize.\n- Use `artificial` to define what evidence belongs in the public article.\n- Use `memetics` to decide whether the page is a new lesson or a duplicate.\n- Use `neurokinetics` to state what the page does not prove.\n- Use `semantic` to remove vague, dramatic, or repetitive wording.\n- Use `calibrants` to keep the article useful without hidden context.\n\n## Next Article Decision: agent-systems/public-wiki-governance/participation-risk-map\n\nA good public version helps future contributors act differently: they can recognize the pattern, check the evidence, and avoid overclaiming. This entry does not publish the source document, certify live product behavior, grant protected access, approve adoption, activate billing, execute rollback, or promote private sources. The boundary for this file is: do not make collective evolution sound risk-free or self-authorizing. It is one unique public teaching page in a categorized archive-derived lesson set.", "ok": true, "requestId": "cfb58585-1575-4662-b673-a3ed167e74d4"}