{"id":"W2006556034","doi":"10.1016/j.jneumeth.2010.04.019","title":"Repeated measurement of the components of attention using two versions of the Attention Network Test (ANT): Stability, isolability, robustness, and reliability","year":2010,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":141,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Robustness (evolution); Reliability (semiconductor); Computer science; Reliability engineering; Attention network; Artificial intelligence; Machine learning; Engineering; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004412936,0.000888066,0.0007939409,0.001214723,0.0005614277,0.0007519213,0.0007507509,0.000816461,0.001449756],"category_scores_gemma":[0.02809636,0.0003213422,0.0007643561,0.0007817523,0.0007689756,0.0008168233,0.0009882739,0.001479657,0.0004349289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000330945,"about_ca_system_score_gemma":0.0005014622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001838717,"about_ca_topic_score_gemma":0.00264326,"domain_scores_codex":[0.9949297,0.001265742,0.0005115364,0.001147507,0.001921197,0.0002242622],"domain_scores_gemma":[0.9786276,0.008607583,0.002568074,0.004202498,0.005227117,0.0007671184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.010127,0.002628361,0.6639324,0.000307766,0.001924686,0.0002604119,0.002855123,0.005544352,0.1441717,0.00186937,0.002086163,0.1642927],"study_design_scores_gemma":[0.0001730296,0.00342233,0.9576576,0.00001616181,0.0003118485,0.0004274783,0.0002010533,0.009289913,0.025878,0.001340779,0.001177052,0.0001048637],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9575078,0.0001405645,0.03829108,0.00005180002,0.0001331217,0.0004867364,0.0006040529,0.0002788873,0.002505967],"genre_scores_gemma":[0.9819444,0.00006608292,0.01430483,0.00007723674,0.0000747229,0.0007710743,0.0009164798,0.0001537282,0.001691499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004412936,"threshold_uncertainty_score":0.02333808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2795538264150725,"score_gpt":0.4326056929260349,"score_spread":0.1530518665109624,"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."}}