{"id":"W2910438939","doi":"10.1126/science.aav0223","title":"Oversight of direct-to-consumer neurotechnologies","year":2019,"lang":"en","type":"article","venue":"Science","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"NeuroDevNet; University of British Columbia","funders":"National Institutes of Health","keywords":"Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001852771,0.00007626642,0.0001086762,0.0002057961,0.00007883455,0.00005120332,0.001045993,0.00002387195,0.00005402516],"category_scores_gemma":[0.000507406,0.0000591662,0.00002740406,0.001027479,0.0005393565,0.000288746,0.0003760582,0.00008306441,0.0004015645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001471531,"about_ca_system_score_gemma":0.00005168082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005346482,"about_ca_topic_score_gemma":6.806724e-7,"domain_scores_codex":[0.9987991,0.00001868521,0.0001115715,0.0004497972,0.0003578058,0.000262993],"domain_scores_gemma":[0.9993089,0.0001442528,0.00005089833,0.0004074627,0.00003588861,0.00005252875],"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":[0.000004076626,0.00001388821,0.001476439,0.000004853879,2.785289e-7,0.000001768174,0.0001317957,0.00007804519,0.9944811,0.001161991,0.000178838,0.002466967],"study_design_scores_gemma":[0.00005797561,0.0001050118,0.002576504,0.00001654443,7.070803e-7,0.000004651275,0.00003295918,0.0003574273,0.9849832,0.0002072664,0.01157972,0.00007799971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808958,0.00002156367,0.00007419963,0.0004654799,0.0006288388,0.0001484713,0.000003689724,0.0001074197,0.01765458],"genre_scores_gemma":[0.9980393,0.000005510011,0.000439658,0.0005566734,0.000006489486,0.000002051623,1.967302e-8,0.000003665937,0.0009466029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01714357,"threshold_uncertainty_score":0.5161433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02148383502574437,"score_gpt":0.2664576738150899,"score_spread":0.2449738387893455,"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."}}