{"id":"W3183224133","doi":"10.1186/s40708-021-00135-3","title":"SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals","year":2021,"lang":"en","type":"article","venue":"Brain Informatics","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Natural Science Foundation of Beijing Municipality; Beijing Municipal Commission of Education; Trent University; Nottingham Trent University","keywords":"Toolbox; Computer science; Artifact (error); MATLAB; Artificial intelligence; Identification (biology); Noise (video); Artificial neural network; Pattern recognition (psychology); Image (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":[0.0008612301,0.001576126,0.0006024848,0.001363309,0.0002323915,0.0009337496,0.001729358,0.0007612997,0.02949011],"category_scores_gemma":[0.004278371,0.0006201764,0.0007339302,0.0005130429,0.0004028917,0.0008535469,0.001398065,0.001415698,0.0154162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00028065,"about_ca_system_score_gemma":0.0008948969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000702651,"about_ca_topic_score_gemma":0.001175285,"domain_scores_codex":[0.9995583,0.00007865129,0.0000504835,0.00009493437,0.0001792441,0.0000383492],"domain_scores_gemma":[0.9987795,0.0006229305,0.0001444637,0.0001241683,0.0002580617,0.00007095493],"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":[0.0009396764,0.0001916943,0.002692929,0.003368294,0.000364275,0.001293972,0.0005328027,0.03497679,0.09071942,0.01628741,0.2188416,0.6297911],"study_design_scores_gemma":[0.0004263973,0.0003050019,0.006358997,0.0006629836,0.0001364761,0.003356982,0.0001249768,0.3687504,0.1441412,0.03234386,0.4431196,0.0002730663],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.002683815,0.000397217,0.8477176,0.0001271725,0.00008693745,0.0001316896,0.003968071,0.1413615,0.003525908],"genre_scores_gemma":[0.05590566,0.001016046,0.8838872,0.0005511895,0.0001207976,0.00146195,0.01242749,0.03251894,0.01211077],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02949011,"threshold_uncertainty_score":0.09865427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03323676528226384,"score_gpt":0.2570023217812291,"score_spread":0.2237655564989653,"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."}}