{"id":"W2588327235","doi":"10.1016/j.brs.2017.01.404","title":"Scalp-based heuristics for locating the nodes of the salience network for use in neurostimulation","year":2017,"lang":"en","type":"article","venue":"Brain stimulation","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University Health Network","funders":"","keywords":"Heuristics; Neurostimulation; Scalp; Dorsolateral prefrontal cortex; Salience (neuroscience); Insula; Neuroscience; Inferior parietal lobule; Psychology; Prefrontal cortex; Computer science; Medicine; Stimulation; Functional magnetic resonance imaging; Anatomy; Cognition","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":[0.001063976,0.0006270632,0.0004735342,0.001456908,0.0007043697,0.001414905,0.000943315,0.0008044557,0.00686808],"category_scores_gemma":[0.01526061,0.0003558657,0.0004166752,0.0008898392,0.0006269891,0.00179124,0.001006391,0.0008279544,0.0007493718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007151909,"about_ca_system_score_gemma":0.001471721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006124502,"about_ca_topic_score_gemma":0.01564701,"domain_scores_codex":[0.9996336,0.0001362428,0.00002170833,0.00008961407,0.00006134119,0.00005754218],"domain_scores_gemma":[0.9970168,0.002107749,0.0001643329,0.0001971352,0.0003831988,0.0001307769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004855288,0.0004905907,0.03718648,0.0008580405,0.0003100154,0.0009522711,0.002654624,0.09129422,0.08296321,0.04869152,0.01819452,0.7115493],"study_design_scores_gemma":[0.0007431197,0.0007728527,0.04642953,0.0002175869,0.0003702033,0.001057286,0.002016812,0.7316118,0.04223695,0.1625956,0.0117786,0.0001697302],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3019861,0.001010182,0.6709504,0.001254723,0.000267739,0.0008592455,0.001173446,0.002259303,0.02023889],"genre_scores_gemma":[0.8558244,0.0001911611,0.1417008,0.00009244344,0.00003917337,0.0001613539,0.0003653781,0.0001859332,0.00143936],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00686808,"threshold_uncertainty_score":0.02297604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0755877928419156,"score_gpt":0.3418566480176709,"score_spread":0.2662688551757553,"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."}}