{"id":"W2006257129","doi":"10.1155/2015/493769","title":"Estimating Latent Attentional States Based on Simultaneous Binary and Continuous Behavioral Measures","year":2015,"lang":"en","type":"article","venue":"Computational Intelligence and Neuroscience","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; National Science Foundation","keywords":"Computer science; Inference; Hidden Markov model; Artificial intelligence; Machine learning; Multinomial distribution; Binary data; Binary number; Probabilistic logic; Pattern recognition (psychology); Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002281521,0.0007195172,0.000917807,0.001033567,0.0003113764,0.001192894,0.001137126,0.0008318226,0.001282376],"category_scores_gemma":[0.01438326,0.0005363254,0.000819431,0.0008732441,0.001123261,0.002217569,0.001293604,0.001717676,0.0002930184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006711608,"about_ca_system_score_gemma":0.000907919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003343803,"about_ca_topic_score_gemma":0.004593238,"domain_scores_codex":[0.9989453,0.000302708,0.00007101052,0.0003781224,0.000195642,0.0001072732],"domain_scores_gemma":[0.9915854,0.005811896,0.001185861,0.000658613,0.0004963657,0.000261909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001391016,0.0008820074,0.1185981,0.0006582027,0.0007283816,0.0003932234,0.0009403504,0.4795316,0.04533232,0.0635371,0.001509849,0.2864978],"study_design_scores_gemma":[0.00002132849,0.0001101081,0.02205469,0.00003484713,0.00005848616,0.00008017572,0.00005009346,0.9368185,0.003470093,0.03701132,0.0002365885,0.00005386923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.19662,0.0002700069,0.8013682,0.0002055787,0.0000276707,0.00005895257,0.0003087325,0.0003207154,0.0008200328],"genre_scores_gemma":[0.9289496,0.0001859254,0.06969161,0.00006650606,0.00002974502,0.0001047871,0.000339358,0.00003663707,0.0005957941],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003343803,"threshold_uncertainty_score":0.01206595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.11235938178572,"score_gpt":0.3267789677954709,"score_spread":0.2144195860097509,"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."}}