{"id":"W4210397188","doi":"10.1155/2022/1573076","title":"Semisupervised Seizure Prediction in Scalp EEG Using Consistency Regularization","year":2022,"lang":"en","type":"article","venue":"Journal of Healthcare Engineering","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of Science and Technology of China; National Natural Science Foundation of China","keywords":"Computer science; Regularization (linguistics); Dropout (neural networks); Artificial intelligence; Machine learning; Consistency (knowledge bases); Deep learning; Electroencephalography; Artificial neural network; Deep neural networks; 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":[0.000422772,0.00009270226,0.0001784881,0.0003110303,0.0001285007,0.00002819257,0.0001700713,0.00003883465,0.00002324596],"category_scores_gemma":[0.0001603331,0.00009494791,0.00005776693,0.0004133559,0.000009850106,0.0002238128,0.00006004858,0.0005197939,3.881786e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000281136,"about_ca_system_score_gemma":0.000121874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001727697,"about_ca_topic_score_gemma":0.000001615502,"domain_scores_codex":[0.9986814,0.000134587,0.0004960778,0.0001412524,0.0003523533,0.0001943083],"domain_scores_gemma":[0.9994977,0.00009782842,0.0001742809,0.00009623474,0.0000555998,0.00007841247],"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":[0.00004248691,0.00006085931,0.002858572,0.0002061221,0.00000651741,0.0001916211,0.001246222,0.5577973,0.4354808,0.0004479578,0.000128899,0.001532689],"study_design_scores_gemma":[0.001181194,0.0005779307,0.005308331,0.0005475917,0.00001432464,0.003402577,0.0006673667,0.9340478,0.05033349,0.0002001987,0.003450926,0.0002682796],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891894,0.0004461904,0.007615036,0.001250986,0.001321912,0.0001098847,0.00001099716,0.00003317002,0.00002242107],"genre_scores_gemma":[0.9982085,0.00001766489,0.00135813,0.000237149,0.0001313146,0.000002313401,9.950932e-7,0.00001632248,0.00002756465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3851473,"threshold_uncertainty_score":0.3871863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02826601243148748,"score_gpt":0.2671460695630629,"score_spread":0.2388800571315754,"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."}}