{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UOAFAR6IHAJUCR2PM6V2T4YW56","short_pith_number":"pith:UOAFAR6I","canonical_record":{"source":{"id":"2401.03401","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-07T07:13:50Z","cross_cats_sorted":[],"title_canon_sha256":"9080776eb87f4f75eae25da75d033284bed4cf085a035f330ba9a9e1f04aecfc","abstract_canon_sha256":"707c6f54cf6e076ecf70263505bac8cb931fb07717160c92a8db4069da51c87c"},"schema_version":"1.0"},"canonical_sha256":"a3805047c8381341474f67aba9f316efa10f1388e39abf5776dbaeaa81957ef7","source":{"kind":"arxiv","id":"2401.03401","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.03401","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"arxiv_version","alias_value":"2401.03401v1","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.03401","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"pith_short_12","alias_value":"UOAFAR6IHAJU","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"pith_short_16","alias_value":"UOAFAR6IHAJUCR2P","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"pith_short_8","alias_value":"UOAFAR6I","created_at":"2026-07-05T07:31:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UOAFAR6IHAJUCR2PM6V2T4YW56","target":"record","payload":{"canonical_record":{"source":{"id":"2401.03401","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-07T07:13:50Z","cross_cats_sorted":[],"title_canon_sha256":"9080776eb87f4f75eae25da75d033284bed4cf085a035f330ba9a9e1f04aecfc","abstract_canon_sha256":"707c6f54cf6e076ecf70263505bac8cb931fb07717160c92a8db4069da51c87c"},"schema_version":"1.0"},"canonical_sha256":"a3805047c8381341474f67aba9f316efa10f1388e39abf5776dbaeaa81957ef7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:31:07.677125Z","signature_b64":"jvWiFxokRqbOsy7pci0kcD16ytvH2lV+JrAaOYaW7bu3eZ3afiAHy9qrSBVbMthcUxzh8pPUnQR4XjhCu82fDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a3805047c8381341474f67aba9f316efa10f1388e39abf5776dbaeaa81957ef7","last_reissued_at":"2026-07-05T07:31:07.676706Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:31:07.676706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.03401","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:31:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PwQvKPt484A7iiTdLv9ttCZFB9rgBsa+Rb3sja0Mbc3d1Jk4Dc1J4UX3y5roLKukeRgnwCRswmctOAEgS2HnAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:31:07.607330Z"},"content_sha256":"ee9c08893ac2f0afc0ddf0b1da39597da65a590dee8876de75a8f80841f7e730","schema_version":"1.0","event_id":"sha256:ee9c08893ac2f0afc0ddf0b1da39597da65a590dee8876de75a8f80841f7e730"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UOAFAR6IHAJUCR2PM6V2T4YW56","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Empirical Study of Large Language Models as Automated Essay Scoring Tools in English Composition__Taking TOEFL Independent Writing Task for Example","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chanjing Zheng, Shaoguang Mao, Wei Xia","submitted_at":"2024-01-07T07:13:50Z","abstract_excerpt":"Large language models have demonstrated exceptional capabilities in tasks involving natural language generation, reasoning, and comprehension. This study aims to construct prompts and comments grounded in the diverse scoring criteria delineated within the official TOEFL guide. The primary objective is to assess the capabilities and constraints of ChatGPT, a prominent representative of large language models, within the context of automated essay scoring. The prevailing methodologies for automated essay scoring involve the utilization of deep neural networks, statistical machine learning techniq"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.03401","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2401.03401/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:31:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zQL2vWWoVgVTOvySuXtcUb1rJhW2QrOCfjahmTM68DPPWxpE5+s/IHhh54XIgILnnQL7g7ySyf1OjBHz2EihBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:31:07.608347Z"},"content_sha256":"3b5e072816dc35c0e69a94da2c05ba6daa68f1d6da2f7591214b5c729ea74b86","schema_version":"1.0","event_id":"sha256:3b5e072816dc35c0e69a94da2c05ba6daa68f1d6da2f7591214b5c729ea74b86"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UOAFAR6IHAJUCR2PM6V2T4YW56/bundle.json","state_url":"https://pith.science/pith/UOAFAR6IHAJUCR2PM6V2T4YW56/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UOAFAR6IHAJUCR2PM6V2T4YW56/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T15:31:07Z","links":{"resolver":"https://pith.science/pith/UOAFAR6IHAJUCR2PM6V2T4YW56","bundle":"https://pith.science/pith/UOAFAR6IHAJUCR2PM6V2T4YW56/bundle.json","state":"https://pith.science/pith/UOAFAR6IHAJUCR2PM6V2T4YW56/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UOAFAR6IHAJUCR2PM6V2T4YW56/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UOAFAR6IHAJUCR2PM6V2T4YW56","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"707c6f54cf6e076ecf70263505bac8cb931fb07717160c92a8db4069da51c87c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-07T07:13:50Z","title_canon_sha256":"9080776eb87f4f75eae25da75d033284bed4cf085a035f330ba9a9e1f04aecfc"},"schema_version":"1.0","source":{"id":"2401.03401","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.03401","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"arxiv_version","alias_value":"2401.03401v1","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.03401","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"pith_short_12","alias_value":"UOAFAR6IHAJU","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"pith_short_16","alias_value":"UOAFAR6IHAJUCR2P","created_at":"2026-07-05T07:31:07Z"},{"alias_kind":"pith_short_8","alias_value":"UOAFAR6I","created_at":"2026-07-05T07:31:07Z"}],"graph_snapshots":[{"event_id":"sha256:3b5e072816dc35c0e69a94da2c05ba6daa68f1d6da2f7591214b5c729ea74b86","target":"graph","created_at":"2026-07-05T07:31:07Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2401.03401/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models have demonstrated exceptional capabilities in tasks involving natural language generation, reasoning, and comprehension. This study aims to construct prompts and comments grounded in the diverse scoring criteria delineated within the official TOEFL guide. The primary objective is to assess the capabilities and constraints of ChatGPT, a prominent representative of large language models, within the context of automated essay scoring. The prevailing methodologies for automated essay scoring involve the utilization of deep neural networks, statistical machine learning techniq","authors_text":"Chanjing Zheng, Shaoguang Mao, Wei Xia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-07T07:13:50Z","title":"Empirical Study of Large Language Models as Automated Essay Scoring Tools in English Composition__Taking TOEFL Independent Writing Task for Example"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.03401","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:ee9c08893ac2f0afc0ddf0b1da39597da65a590dee8876de75a8f80841f7e730","target":"record","created_at":"2026-07-05T07:31:07Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"707c6f54cf6e076ecf70263505bac8cb931fb07717160c92a8db4069da51c87c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-07T07:13:50Z","title_canon_sha256":"9080776eb87f4f75eae25da75d033284bed4cf085a035f330ba9a9e1f04aecfc"},"schema_version":"1.0","source":{"id":"2401.03401","kind":"arxiv","version":1}},"canonical_sha256":"a3805047c8381341474f67aba9f316efa10f1388e39abf5776dbaeaa81957ef7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a3805047c8381341474f67aba9f316efa10f1388e39abf5776dbaeaa81957ef7","first_computed_at":"2026-07-05T07:31:07.676706Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:31:07.676706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jvWiFxokRqbOsy7pci0kcD16ytvH2lV+JrAaOYaW7bu3eZ3afiAHy9qrSBVbMthcUxzh8pPUnQR4XjhCu82fDw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:31:07.677125Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.03401","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ee9c08893ac2f0afc0ddf0b1da39597da65a590dee8876de75a8f80841f7e730","sha256:3b5e072816dc35c0e69a94da2c05ba6daa68f1d6da2f7591214b5c729ea74b86"],"state_sha256":"e92d5b3d199a21b59a82f74889af4751fbd8cc7effa3e996590cc9aa7e80e765"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v+vPVf6SHVsN1otVSVVv8LlQtrdk0kknTIjZPwqFWVlI+GY8tqZKgfLRVGfo0hAbp/hYIka3JUiHj8IjJezjDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:31:07.616648Z","bundle_sha256":"41b0312013823384225635340dc7df2ba262f08c00bca5adfcc1aa6e204480e3"}}