{"id":"W3215712506","doi":"10.1016/j.brs.2021.10.452","title":"Predicting seizure response to VNS through connectomic profiling","year":2021,"lang":"en","type":"article","venue":"Brain stimulation","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Profiling (computer programming); Medicine; Psychology; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002019978,0.0004521266,0.0003036385,0.000678996,0.00009146285,0.0004205319,0.0001028153,0.0002557773,0.001014036],"category_scores_gemma":[0.001069744,0.00005761307,0.000257481,0.0004381392,0.0001390859,0.0002246788,0.0001873192,0.0002304966,0.0002252977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001156733,"about_ca_system_score_gemma":0.0001683865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001202733,"about_ca_topic_score_gemma":0.002491893,"domain_scores_codex":[0.9999179,0.00002254492,0.000007417782,0.00002019453,0.00001594653,0.00001600143],"domain_scores_gemma":[0.9997068,0.0001619697,0.00005547557,0.00001474851,0.00003653486,0.00002443479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003248482,0.0002696649,0.5270936,0.0003397482,0.0007513408,0.001219559,0.000177128,0.02040798,0.2108938,0.0006010279,0.003003438,0.2319942],"study_design_scores_gemma":[0.00007914581,0.00109534,0.8658382,0.00009382838,0.0005640597,0.002250812,0.0004930054,0.09310199,0.02965838,0.003803721,0.002974383,0.0000472257],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850379,0.0008946074,0.01003885,0.0002220551,0.00003549177,0.00003971608,0.001962625,0.0001406676,0.001628151],"genre_scores_gemma":[0.995465,0.0003881334,0.002328666,0.00008104193,0.00002842119,0.00002840366,0.001185725,0.00001810392,0.0004764037],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001202733,"threshold_uncertainty_score":0.00339222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04774637259227133,"score_gpt":0.3264319399359623,"score_spread":0.2786855673436909,"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."}}