{"id":"W3150247581","doi":"10.18280/ts.380102","title":"Depression Detection Based on Geometrical Features Extracted from SODP Shape of EEG Signals and Binary PSO","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Teknikal Malaysia Melaka; Islamic Azad University","keywords":"Centroid; Pattern recognition (psychology); Electroencephalography; Artificial intelligence; Support vector machine; Mathematics; Particle swarm optimization; Computer science; Algorithm; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001522043,0.0001885512,0.000232464,0.0002292674,0.0001251719,0.00008613292,0.0001701056,0.000102952,0.0008240778],"category_scores_gemma":[0.0001618763,0.0001584589,0.00008617453,0.0004453431,0.00007262175,0.0001439745,0.00007347093,0.0002201725,0.000007303942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002399715,"about_ca_system_score_gemma":0.00003255072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002242352,"about_ca_topic_score_gemma":0.000004934016,"domain_scores_codex":[0.9981826,0.0002397144,0.0003064272,0.000549935,0.0004963984,0.0002249231],"domain_scores_gemma":[0.9985309,0.001000105,0.000133164,0.0001742074,0.00005681651,0.0001047618],"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":[0.0002442515,0.0003910356,0.0007944254,0.00002187657,0.000009759185,0.00006345146,0.00008865501,0.001026756,0.9455537,0.00000950207,0.0002986632,0.05149792],"study_design_scores_gemma":[0.0008932737,0.0004274411,0.08070303,0.0001013819,0.00002010266,0.00001044543,0.00002507428,0.05371602,0.8634988,0.00007667956,0.0003752625,0.0001524654],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946377,0.0002191771,0.004186674,0.0002288589,0.0001672619,0.0001640636,0.00006219404,0.00006696251,0.0002670533],"genre_scores_gemma":[0.9985893,0.00001423799,0.0004433923,0.0007731725,0.00009033987,0.00001121328,0.00001468326,0.00001548195,0.00004820097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08205489,"threshold_uncertainty_score":0.9023074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0249951108368729,"score_gpt":0.262387293375675,"score_spread":0.2373921825388021,"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."}}