{"id":"W4396863749","doi":"10.31234/osf.io/9fyxb","title":"Concurrent TMS-fMRI: An international consensus and functional guide for current and future researchers","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rogue Research (Canada)","funders":"Biotechnology and Biological Sciences Research Council; Medical Research Council","keywords":"Causal inference; Inference; Brain research; Cognitive science; Cognition; Neuroscience; Computer science; Cognitive neuroscience; Psychology; Functional connectivity; Data science; Artificial intelligence; Medicine","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":[0.05723754,0.003186698,0.003266716,0.008849914,0.00194812,0.006600281,0.009814464,0.01058712,0.009373683],"category_scores_gemma":[0.07903421,0.002044252,0.002417043,0.006850795,0.009272712,0.01073093,0.0072492,0.01733723,0.01678325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002694288,"about_ca_system_score_gemma":0.01179674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002336861,"about_ca_topic_score_gemma":0.003162344,"domain_scores_codex":[0.9811434,0.00951981,0.004036136,0.001378822,0.003411938,0.000509968],"domain_scores_gemma":[0.9321105,0.03764667,0.002711556,0.007848991,0.01661243,0.003069818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001930641,0.000225771,0.000386687,0.004015024,0.0001223498,0.0005006867,0.001205603,0.001582799,0.003455171,0.05370888,0.6399916,0.2946124],"study_design_scores_gemma":[0.00006310512,0.0001028609,0.0005094783,0.003442475,0.00005579257,0.001286613,0.0005387269,0.00139078,0.001358526,0.1152489,0.8758907,0.00011189],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001070631,0.1729312,0.5699603,0.2048516,0.02297362,0.002066237,0.002392097,0.004839931,0.01891444],"genre_scores_gemma":[0.008039332,0.1046586,0.7812331,0.05879375,0.01570944,0.009588975,0.003394363,0.003620139,0.01496227],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05723754,"threshold_uncertainty_score":0.3027047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1867927991331731,"score_gpt":0.4023454736800709,"score_spread":0.2155526745468978,"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."}}