{"id":"W4220704048","doi":"10.3390/s22072575","title":"LASSO Homotopy-Based Sparse Representation Classification for fNIRS-BCI","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"National Centre of Robotics and Automation","keywords":"Lasso (programming language); Brain–computer interface; Representation (politics); Homotopy; Artificial intelligence; Computer science; Pattern recognition (psychology); Machine learning; Mathematics; Psychology; Neuroscience; Electroencephalography; Pure mathematics; Programming language","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":[0.0001925051,0.00008106316,0.0001482048,0.0001023495,0.0001575081,0.00001660692,0.00005284725,0.00003070935,0.0001330719],"category_scores_gemma":[0.0001665085,0.00008066435,0.00009395035,0.0001823862,0.0000452783,0.00002623955,0.00001633182,0.0001599477,0.00001210977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001331096,"about_ca_system_score_gemma":0.00005148616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003265268,"about_ca_topic_score_gemma":0.000001555341,"domain_scores_codex":[0.9991469,0.00004974369,0.0001633501,0.0002451487,0.0002209383,0.0001739333],"domain_scores_gemma":[0.9994196,0.00009244571,0.00005929415,0.0002929405,0.00007257768,0.00006309428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00297516,0.002198019,0.08321114,0.0003595832,0.0001801935,0.0001346847,0.00097552,0.00166953,0.7395718,0.03083738,0.1173362,0.02055081],"study_design_scores_gemma":[0.004516145,0.002300822,0.04789591,0.00006465202,0.0003586872,0.00007932068,0.001499348,0.4060443,0.4041024,0.004422038,0.1281425,0.000573859],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9697314,0.00002852942,0.007571587,0.01185789,0.0001930303,0.001017843,0.00004050076,0.0005184568,0.009040757],"genre_scores_gemma":[0.9723761,0.000004693794,0.0236117,0.0006820906,0.00008714521,0.0002005678,0.0001526392,0.00002454353,0.002860509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4043748,"threshold_uncertainty_score":0.3289397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05753577506108547,"score_gpt":0.3687424682145611,"score_spread":0.3112066931534756,"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."}}