{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3395","dataset_id":"ds004851","associated_paper_doi":null,"authors":["Tony Johnson","Stephen Gordon","Jon Touryan","Kevin King"],"bids_version":"1.8.0","contact_info":["Kevin King"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds004851.v2.1.0","datatypes":["eeg"],"demographics":{"subjects_count":66,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds004851","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"71210fead8b09e3070405d92e1ee1ad638a088c9b3ffc447f522983e17708bc2","license":"CC0","n_contributing_labs":null,"name":"HID","readme":"HID dataset","recording_modality":["eeg"],"senior_author":"Kevin King","sessions":[],"size_bytes":60057550495,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["HID"],"timestamps":{"digested_at":"2026-04-22T12:27:03.378418+00:00","dataset_created_at":"2023-11-14T15:33:49.960Z","dataset_modified_at":"2024-07-09T03:15:38.000Z"},"total_files":66,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004851","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.tsv","task-HID_events.json"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"1ca962724cd9bd00","model":"openai/gpt-5.2","tagged_at":"2026-01-20T17:34:08.949845+00:00"},"tags":{"pathology":["Unknown"],"modality":["Unknown"],"type":["Unknown"],"confidence":{"pathology":0.35,"modality":0.35,"type":0.35},"reasoning":{"few_shot_analysis":"Across the few-shot examples, labels are assigned only when metadata contains concrete facts about (a) recruited population (e.g., \"Parkinsons disease\", \"mTBI\"), (b) stimulus/input modality (e.g., auditory tones, visual dots, resting eyes-closed), and (c) study aim/type (e.g., oddball/perception, reinforcement learning/decision-making, resting-state). Here, the provided dataset metadata does not contain any such facts, so the few-shot examples mainly guide the convention that in the absence of task/population/stimulus detail, we should select \"Unknown\" rather than guessing.","metadata_analysis":"The only available metadata is the README line: \"HID dataset\". There are no descriptions of participants, diagnoses, tasks, stimuli, recording conditions (rest/sleep), or events.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata SAYS only \"HID dataset\" (no diagnosis/population). Few-shot pattern SUGGESTS using specific pathology labels only when explicitly stated (e.g., \"Parkinsons disease\", \"epilepsy\", \"healthy participants\"). ALIGNMENT: cannot assess; no facts present → choose Unknown.\nModality: Metadata SAYS only \"HID dataset\" (no stimulus channel described). Few-shot pattern SUGGESTS mapping based on described stimuli/condition (auditory/visual/rest/sleep/etc.). ALIGNMENT: cannot assess; no facts present → choose Unknown.\nType: Metadata SAYS only \"HID dataset\" (no paradigm/aim described). Few-shot pattern SUGGESTS mapping based on explicit task aim (resting-state, sleep, motor imagery, learning, etc.). ALIGNMENT: cannot assess; no facts present → choose Unknown.","decision_summary":"Pathology top-2 candidates: (1) Unknown — supported by absence of any population/diagnosis statement (only \"HID dataset\"); (2) Healthy — possible in many EEG datasets but unsupported here. Winner: Unknown (no evidence). Confidence 0.35 because there is effectively zero discriminative metadata.\nModality top-2 candidates: (1) Unknown — no stimulus/condition described beyond \"HID dataset\"; (2) Resting State — common default but not stated. Winner: Unknown. Confidence 0.35 due to no modality evidence.\nType top-2 candidates: (1) Unknown — no task/aim described; (2) Other — could be methodological, but no support. Winner: Unknown. Confidence 0.35 due to no type evidence."}},"nemar_citation_count":0,"computed_title":"HID","nchans_counts":[{"val":72,"count":66}],"sfreq_counts":[{"val":2048.0,"count":66}],"stats_computed_at":"2026-04-22T23:16:00.308559+00:00","total_duration_s":66898.2822265625,"canonical_name":null,"name_confidence":0.97,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"canonical","author_year":"Johnson2023_HID"}}