{"id":"W3159928448","doi":"10.3390/s21092953","title":"Custom-Fitted In- and Around-the-Ear Sensors for Unobtrusive and On-the-Go EEG Acquisitions: Development and Validation","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; McGill University; Centre for Interdisciplinary Research in Music Media and Technology","funders":"Mitacs","keywords":"Electroencephalography; Wearable computer; Ear canal; Computer science; Latency (audio); Silicone; Acoustics; Biomedical engineering; Engineering; Materials science; Embedded system; Telecommunications; Neuroscience; Psychology; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001310844,0.001082767,0.0003976316,0.0005816363,0.0001662755,0.0003829001,0.001521777,0.000885591,0.002070971],"category_scores_gemma":[0.002785372,0.0003349131,0.000389962,0.0002807576,0.0004791945,0.0005068849,0.0006163453,0.0003382252,0.0006303985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002323301,"about_ca_system_score_gemma":0.0004691587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003540895,"about_ca_topic_score_gemma":0.0008594749,"domain_scores_codex":[0.9988862,0.0002113748,0.00009748947,0.0002145052,0.0005196824,0.00007084243],"domain_scores_gemma":[0.9985237,0.0003339874,0.0002628151,0.0003317589,0.0004527762,0.00009496517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003040038,0.0004182924,0.002999351,0.001015258,0.00005615745,0.0003881132,0.0002732763,0.002505452,0.9348965,0.0004871518,0.0006535469,0.05600282],"study_design_scores_gemma":[0.0001084283,0.005006098,0.01832024,0.0001157845,0.0001383431,0.002313873,0.0001822112,0.01167865,0.947952,0.0002226121,0.01389479,0.00006705466],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.515245,0.001307661,0.4753262,0.0001873275,0.000367924,0.002755013,0.001046265,0.001610539,0.002154101],"genre_scores_gemma":[0.6478238,0.001126616,0.3435868,0.0001570476,0.00005211773,0.001791891,0.000685203,0.0001802425,0.004596254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002070971,"threshold_uncertainty_score":0.006932497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03463747338590123,"score_gpt":0.2744181826277855,"score_spread":0.2397807092418843,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}