{"id":"W7014911666","doi":"","title":"Réseau génératif antagoniste pour la traduction de signaux de capteurs avec application à l'ECG","year":2022,"lang":"fr","type":"other","venue":"Archipelago (Université du Québec à Montréal)","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Frequency selectivity; Spectral analysis; Complementary sequences","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006146826,0.0006475411,0.0008302949,0.0006845008,0.0008609593,0.00005933943,0.0005986458,0.0004364221,0.006053721],"category_scores_gemma":[0.0001260449,0.0007846219,0.0006305284,0.0006555609,0.0003391584,0.0001336576,0.0002159776,0.001233167,0.0005622849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003808359,"about_ca_system_score_gemma":0.002300134,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3750609,"about_ca_topic_score_gemma":0.1871966,"domain_scores_codex":[0.9964477,0.0007087145,0.0004223711,0.0009510265,0.0005596441,0.0009104726],"domain_scores_gemma":[0.9974666,0.0004474662,0.0004656783,0.0008848201,0.00009536475,0.0006400578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006394785,0.001377734,0.06302293,0.0007487067,0.002709771,0.002776296,0.1425634,0.004312194,0.02187848,0.00559911,0.0158558,0.7385161],"study_design_scores_gemma":[0.003770839,0.0005122348,0.02313636,0.0005194101,0.005375058,0.001301543,0.0820823,0.09192573,0.0005569005,0.001270898,0.7879668,0.001581942],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7151565,0.02354934,0.09419185,0.03004671,0.001152215,0.001574602,0.0001854849,0.0008286645,0.1333146],"genre_scores_gemma":[0.79108,0.004091354,0.003744596,0.0002765001,0.002245399,0.00006616885,0.0002327928,0.0004035607,0.1978596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.772111,"threshold_uncertainty_score":0.9994605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004659483127695275,"score_gpt":0.1877301703482684,"score_spread":0.1830706872205732,"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."}}