CH
ENT-00002402 · Modèle IA

CHGNet

CHGNet is a AI model associated with UC Berkeley, classified in LXKeys.world as Scientific / Biomedical Model.

Niveau V PersistantActifDocumenté
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Vue d’ensemble

CHGNet is an AI model or research system associated with UC Berkeley. It is documented as crystal graph neural network for materials modeling.

Chronologie

  1. 2023Initial model publication or release

    CHGNet entered the documented public record in 2023. This event is retained at the precision supported by the Entry’s reviewed source history.

Capacités

Model inference or generationResearch or product evaluationVersioned technical documentationIntegration into model or product ecosystems

Limites connues

Model behavior depends on version, deployment settings and usage context.Capabilities should be interpreted through the linked model card, official documentation or research source.
Détail technique et structuré

Description technique

Structured LXKeys.world registry record for CHGNet. Entity type: AI Model; classification: Scientific / Biomedical Model; creator/organization context: Ceder Group. Canonical source anchor: https://github.com/CederGroupHub/chgnet. The record tracks source authority, first public appearance, timeline, capabilities, limitations, registry status and graph relationships. Automatic refresh is limited to sources explicitly classified as OFFICIAL and enabled for updates; documentary and research references remain non-authoritative unless reviewed.

Tags contrôlés

Scientific AIAI ModelMaterialsScientific AI Model
Graphe relationnel

CHGNet

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CHGNet
CréateurSortante
Ceder Group

Ceder Group is documented as creator, contributor or originating team for CHGNet.

Organisation associéeSortante
UC Berkeley

UC Berkeley is the organization or institutional context associated with CHGNet.

ClassificationSortante
Scientific AI Model

CHGNet is classified as Scientific AI Model.

Couche lisible par machine

Données structurées de l’entrée pour les outils humains, les systèmes IA et les clients machine.

{
    "@context": [
        "https://schema.org",
        {
            "lxw": "https://lxkeys.world/schema/"
        }
    ],
    "@type": "Thing",
    "identifier": "ENT-00002402",
    "name": "CHGNet",
    "alternateName": [],
    "additionalType": {
        "category": "Models",
        "type": "AI Model",
        "subtype": "",
        "lxkeysEntity": false
    },
    "description": "CHGNet is a AI model associated with UC Berkeley, classified in LXKeys.world as Scientific / Biomedical Model.",
    "creator": "Ceder Group",
    "url": "https://lxkeys.world/entry.php?id=ENT-00002402&lang=fr",
    "sameAs": "https://github.com/CederGroupHub/chgnet",
    "image": "",
    "lxkeysWorld": {
        "worldId": "ENT-00002402",
        "kind": "Models",
        "type": "AI Model",
        "subtype": "",
        "classification": "Scientific / Biomedical Model",
        "organization": "UC Berkeley",
        "originContext": "AI model repository",
        "firstPublicAppearance": "2023",
        "currentStatus": "Active",
        "documentationStatus": "Documented",
        "documentationIndex": {
            "total": 88,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 25,
            "level": "Level V Persistent"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-17T01:33:48+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-22 T-4",
            "updated_utc": "2026-06-17T01:33:48+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-22 T-4"
        },
        "facts": [],
        "capabilities": [
            "Model inference or generation",
            "Research or product evaluation",
            "Versioned technical documentation",
            "Integration into model or product ecosystems"
        ],
        "limitations": [
            "Model behavior depends on version, deployment settings and usage context.",
            "Capabilities should be interpreted through the linked model card, official documentation or research source."
        ],
        "tags": [
            "Scientific AI",
            "AI Model",
            "Materials",
            "Scientific AI Model"
        ],
        "timeline": [
            {
                "date": "2023",
                "title": "Initial model publication or release",
                "description": "CHGNet entered the documented public record in 2023. This event is retained at the precision supported by the Entry’s reviewed source history.",
                "source_url": "https://github.com/CederGroupHub/chgnet",
                "verification_status": "source_backed_curated_baseline"
            }
        ],
        "relationships": [
            {
                "target": "Ceder Group",
                "type": "Creator",
                "description": "Ceder Group is documented as creator, contributor or originating team for CHGNet.",
                "evidence_level": "documentary"
            },
            {
                "target": "UC Berkeley",
                "type": "Associated organization",
                "description": "UC Berkeley is the organization or institutional context associated with CHGNet.",
                "evidence_level": "documentary"
            },
            {
                "target": "Scientific AI Model",
                "type": "Classification",
                "description": "CHGNet is classified as Scientific AI Model.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "Official documentation",
                "url": "https://github.com/CederGroupHub/chgnet",
                "source_type": "Model Card / Official Source",
                "verification_status": "verified",
                "authority": "TRUSTED_PRIMARY",
                "role": "code_repository",
                "update_enabled": false,
                "authority_basis": "curated-corpus-refresh-2026-09-08"
            }
        ],
        "canonical": [],
        "imageMeta": []
    }
}
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