{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3403","dataset_id":"ds005571","associated_paper_doi":null,"authors":["María Paz Martínez-Molina","Alejandra Figueroa-Vargas","Francisco Zamorano","Pablo Billeke"],"bids_version":"1.9.0","contact_info":["Pablo Billeke"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds005571.v1.0.1","datatypes":["eeg"],"demographics":{"subjects_count":24,"ages":[31,24,33,23,33,22,30,24,22,21,32,28,23,19,26,21,26,26,25,19,25,23,32,21,23,26,27,22,27],"age_min":19,"age_max":33,"age_mean":25.310344827586206,"species":null,"sex_distribution":{"m":14,"f":15},"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds005571","osf_url":null,"github_url":null,"paper_url":null},"funding":["ANID FONDECYT 11140535","ANID FONDECYT 1181295","ANID FONDECYT 1211227","ANID FONDEQUIP EQM150076"],"ingestion_fingerprint":"cc37c74db69e4b128a6a1613d2530e462e54b087acd65f46c2daa399593f1929","license":"CC0","n_contributing_labs":null,"name":"Expectation of Conflict Stimuli ","readme":null,"recording_modality":["eeg"],"senior_author":"Pablo Billeke","sessions":[],"size_bytes":67959727373,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["gnga","gngb"],"timestamps":{"digested_at":"2026-04-22T12:28:38.275804+00:00","dataset_created_at":"2024-10-11T22:56:27.790Z","dataset_modified_at":"2024-11-11T14:35:45.000Z"},"total_files":45,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005571","raw_key":"dataset_description.json","dep_keys":["CHANGES","participants.json","participants.tsv","task-gnga_events.json","task-gngb_events.json","task-msit_events.json"]},"tagger_meta":{"config_hash":"3557b68bca409f28","metadata_hash":"4dfd2049d20a1353","model":"openai/gpt-5.2","tagged_at":"2026-04-07T09:32:40.872789+00:00"},"tags":{"pathology":["Healthy"],"modality":["Unknown"],"type":["Attention"],"confidence":{"pathology":0.7,"modality":0.5,"type":0.7},"reasoning":{"few_shot_analysis":"Most similar few-shot by task construct is: (1) “EEG: DPX Cog Ctl Task in Acute Mild TBI” (few-shot) labeled Type=Attention and Modality=Visual, because it is a cognitive-control/conflict/expectancy task with explicit visual cues/probes. The current dataset title “Expectation of Conflict Stimuli” and task names “gnga/gngb” suggest a Go/No-Go style conflict/response-inhibition paradigm, which by convention in the few-shot set would map to Attention (cognitive control). However, unlike the DPX example, this dataset’s metadata does not explicitly state the sensory modality (visual vs auditory), so few-shot conventions cannot supply that fact.","metadata_analysis":"Key available metadata is sparse. Population info: “Subjects: 24; Sex: {'m': 14, 'f': 15}; Age range: 19-33” (participants_overview) with no mention of any diagnosis/grouping. Task info: tasks are listed as “gnga” and “gngb” (tasks field). Study framing: title is “Expectation of Conflict Stimuli” (title). No readme/task description is provided that states stimulus type (e.g., visual images, tones).","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: (1) Metadata says: no clinical recruitment is stated; only “Subjects: 24… Age range: 19-33”. (2) Few-shot pattern suggests: when no disorder is mentioned, label as Healthy (normative cohort). (3) ALIGN (no conflict).\n\nModality: (1) Metadata says: tasks “gnga”, “gngb” and title “Expectation of Conflict Stimuli” but does not specify whether stimuli are visual, auditory, etc. (2) Few-shot pattern suggests: cognitive-control tasks like DPX are often Visual, but this is not a stated fact here. (3) CONFLICT/INSUFFICIENT: few-shot can’t override missing modality facts; therefore choose Unknown.\n\nType: (1) Metadata says: “Expectation of Conflict Stimuli” and tasks “gnga/gngb” (suggesting go/no-go variants, i.e., conflict/response inhibition/expectancy). (2) Few-shot pattern suggests: conflict/expectancy/cognitive control tasks map to Attention (e.g., DPX task labeled Attention). (3) ALIGN (construct-level match; no contradictory metadata).","decision_summary":"Top-2 candidates per category:\n\nPathology:\n- Healthy (selected): Supported by absence of any diagnosis and typical normative demographics: “Subjects: 24… Age range: 19-33”.\n- Unknown (runner-up): Because the metadata never explicitly says “healthy controls”.\nAlignment: aligned with few-shot convention that non-clinical cohorts default to Healthy.\n\nModality:\n- Unknown (selected): No explicit stimulus-channel description beyond task names “gnga/gngb” and title “Expectation of Conflict Stimuli”.\n- Visual (runner-up): Go/No-Go/conflict tasks are commonly visually cued (supported only by contextual inference and few-shot conventions like DPX=Visual).\nAlignment: insufficient explicit metadata; few-shot cannot supply missing facts.\n\nType:\n- Attention (selected): “Expectation of Conflict Stimuli” implies conflict monitoring/cognitive control; “gnga/gngb” likely Go/No-Go variants (response inhibition/expectancy), which matches few-shot mapping of cognitive control tasks to Attention.\n- Decision-making (runner-up): Could be framed as expectancy/choice under conflict, but no explicit valuation/policy-learning framing is provided.\nAlignment: consistent with few-shot convention (DPX cognitive control labeled Attention).\n\nConfidence justification: Pathology moderate (no diagnosis stated, but clear non-clinical listing); Modality low (no direct stimulus info); Type moderate (title strongly indicates conflict/cognitive control, supported by task naming but without explicit task description)."}},"nemar_citation_count":1,"computed_title":"Expectation of Conflict Stimuli","nchans_counts":[{"val":66,"count":41},{"val":67,"count":4}],"sfreq_counts":[{"val":5000.0,"count":45}],"stats_computed_at":"2026-04-22T23:16:00.310636+00:00","total_duration_s":null,"canonical_name":null,"name_confidence":0.63,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"author_year","author_year":"MartinezMolina2024"}}