{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ICGFYYDWXEDXWMXUCMAWCQZLWF","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":"54964b2ac5f801834eeb642713750a40d5274e6501614f64ab203e66016e09c1","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2026-08-10T22:18:33Z","title_canon_sha256":"265d3a3e5112c67dd7e7748be57a8926afa6b3b950ac864c2958e94849a667b5"},"schema_version":"1.0","source":{"id":"2608.10276","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.10276","created_at":"2026-08-12T00:23:14Z"},{"alias_kind":"arxiv_version","alias_value":"2608.10276v1","created_at":"2026-08-12T00:23:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.10276","created_at":"2026-08-12T00:23:14Z"},{"alias_kind":"pith_short_12","alias_value":"ICGFYYDWXEDX","created_at":"2026-08-12T00:23:14Z"},{"alias_kind":"pith_short_16","alias_value":"ICGFYYDWXEDXWMXU","created_at":"2026-08-12T00:23:14Z"},{"alias_kind":"pith_short_8","alias_value":"ICGFYYDW","created_at":"2026-08-12T00:23:14Z"}],"graph_snapshots":[{"event_id":"sha256:ff8a8d55673e4e89001832d3e9808b3c24ab8a5c06f07a56c9be12aeedb84cdd","target":"graph","created_at":"2026-08-12T00:23:14Z","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/2608.10276/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Student-generated metaphors about mathematics can reveal students' attitudes, beliefs, identities, and experiences, but human expert coding of these thematically and semantically complex open-ended responses is time-intensive and difficult to scale. This study examines whether LoRA-based supervised fine-tuning of large language models (LLMs) can improve their performance on codebook-guided coding tasks for student mathematics metaphors. We used a human-coded corpus of 2,265 Grade 6-8 responses to food- and animal-based metaphor prompts and instructed the LLMs to perform two coding tasks: valen","authors_text":"Jinfa Cai, Liang Zhang, Stephen Hwang, Yue Ma","cross_cats":["cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2026-08-10T22:18:33Z","title":"Fine-Tuning Large Language Models for Codebook-Guided Coding of Students' Mathematics Metaphor Responses"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.10276","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:dd8a56adf404105b2f5f79ca3012740e62bfcb5111ff4c80a5cf9e33c89fb795","target":"record","created_at":"2026-08-12T00:23:14Z","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":"54964b2ac5f801834eeb642713750a40d5274e6501614f64ab203e66016e09c1","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2026-08-10T22:18:33Z","title_canon_sha256":"265d3a3e5112c67dd7e7748be57a8926afa6b3b950ac864c2958e94849a667b5"},"schema_version":"1.0","source":{"id":"2608.10276","kind":"arxiv","version":1}},"canonical_sha256":"408c5c6076b9077b32f4130161432bb172e807eedcb050a4d1a823dbd771bf89","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"408c5c6076b9077b32f4130161432bb172e807eedcb050a4d1a823dbd771bf89","first_computed_at":"2026-08-12T00:23:14.690144Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-12T00:23:14.690144Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nqMiZqdLbyOr8U+X7FsjOu9PSd35wFNnvGLD3rQRyeOJnJXse4tw7ULyPQ3qo01OAlIt3yPvNd+xYNOR96wfDg==","signature_status":"signed_v1","signed_at":"2026-08-12T00:23:14.691821Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.10276","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dd8a56adf404105b2f5f79ca3012740e62bfcb5111ff4c80a5cf9e33c89fb795","sha256:ff8a8d55673e4e89001832d3e9808b3c24ab8a5c06f07a56c9be12aeedb84cdd"],"state_sha256":"1f2c1b2299642cd075889a10afaaaeb771f72f477f02ea7432788faab94e5e31"}