{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:OA6ZDDBAOCKYBVCXQ35G337XNC","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":"6fb0f3689242b70f5df1536e58b03f970909d63e1156f634b937d8ef5eecbc15","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-21T00:02:28Z","title_canon_sha256":"769cb73d4a57e5e21cc05e5b0eaabaa32962014c0dfb525be45d24ba2ceddeff"},"schema_version":"1.0","source":{"id":"2502.15107","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.15107","created_at":"2026-07-05T10:17:56Z"},{"alias_kind":"arxiv_version","alias_value":"2502.15107v1","created_at":"2026-07-05T10:17:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.15107","created_at":"2026-07-05T10:17:56Z"},{"alias_kind":"pith_short_12","alias_value":"OA6ZDDBAOCKY","created_at":"2026-07-05T10:17:56Z"},{"alias_kind":"pith_short_16","alias_value":"OA6ZDDBAOCKYBVCX","created_at":"2026-07-05T10:17:56Z"},{"alias_kind":"pith_short_8","alias_value":"OA6ZDDBA","created_at":"2026-07-05T10:17:56Z"}],"graph_snapshots":[{"event_id":"sha256:c6831647023e3019c638f97238ebc030821d12ea16cc7b92eb4ef9e9e3c66508","target":"graph","created_at":"2026-07-05T10:17:56Z","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/2502.15107/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study introduces a specialized pipeline designed to classify the concentration state of an individual student during online learning sessions by training a custom-tailored machine learning model. Detailed protocols for acquiring and preprocessing EEG data are outlined, along with the extraction of fifty statistical features from five EEG signal bands: alpha, beta, theta, delta, and gamma. Following feature extraction, a thorough feature selection process was conducted to optimize the data inputs for a personalized analysis. The study also explores the benefits of hyperparameter fine-tunin","authors_text":"Amine Nait-ali, Hazem Zein, Mohamad Najafi, Zewen Zhuo","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-21T00:02:28Z","title":"Assessing a Single Student's Concentration on Learning Platforms: A Machine Learning-Enhanced EEG-Based Framework"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.15107","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":"sha256:2387c537892aa50d353b185649cfa2988728eeae0784d0de4b9d51c7744e06dc","target":"record","created_at":"2026-07-05T10:17:56Z","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":"6fb0f3689242b70f5df1536e58b03f970909d63e1156f634b937d8ef5eecbc15","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-21T00:02:28Z","title_canon_sha256":"769cb73d4a57e5e21cc05e5b0eaabaa32962014c0dfb525be45d24ba2ceddeff"},"schema_version":"1.0","source":{"id":"2502.15107","kind":"arxiv","version":1}},"canonical_sha256":"703d918c20709580d45786fa6deff76892fa09f8ed6a76c5784c23479ccf88d5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"703d918c20709580d45786fa6deff76892fa09f8ed6a76c5784c23479ccf88d5","first_computed_at":"2026-07-05T10:17:56.272441Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:17:56.272441Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MIIhUEYEQcm6XFZTah3KPv3eBD+1kWJx/TGJLj2v28Jb6etCyGrK4iCFHENOT6kLJ0zb6rmNJlVe9l7fyCTeCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:17:56.272863Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.15107","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2387c537892aa50d353b185649cfa2988728eeae0784d0de4b9d51c7744e06dc","sha256:c6831647023e3019c638f97238ebc030821d12ea16cc7b92eb4ef9e9e3c66508"],"state_sha256":"b0c80e05d1ebae86c5e209c02ffda1fc048c5c5aacd4d1774d368a977c80e744"}