{"id":"W6912363775","doi":"10.5281/zenodo.4624435","title":"Data for: Structure can predict function in the human brain: A graph neural network deep learning model of functional connectivity and centrality based on structural connectivity","year":2021,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Centrality; Deep learning; Artificial neural network; Graph; Function (biology); Functional connectivity; Graph theory; Pattern recognition (psychology)","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":[0.0004509641,0.0005005944,0.0002747332,0.000565085,0.0003236274,0.0007545706,0.0008642145,0.001171308,0.004096895],"category_scores_gemma":[0.004139001,0.0002319402,0.0004956158,0.000679443,0.0005322447,0.001483744,0.0006102648,0.00130647,0.0007425677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007997779,"about_ca_system_score_gemma":0.0006146409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008477905,"about_ca_topic_score_gemma":0.01023686,"domain_scores_codex":[0.9998863,0.00002452659,0.000004693346,0.00004353589,0.00003046373,0.00001054646],"domain_scores_gemma":[0.999474,0.0002266676,0.00005975226,0.00008063891,0.0001210349,0.00003789232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005994835,0.0002947373,0.01349312,0.0003875572,0.0002442127,0.0003494383,0.0003167201,0.4867299,0.01346478,0.1699603,0.08120903,0.2329507],"study_design_scores_gemma":[0.00003134692,0.00003616703,0.002827203,0.00002835103,0.00002719343,0.00007016326,0.00001859258,0.9015116,0.00249499,0.08897177,0.003957666,0.00002491101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.2259213,0.001139447,0.7376443,0.01135551,0.0005716265,0.0001169379,0.01272141,0.002546155,0.007983179],"genre_scores_gemma":[0.8891407,0.0006761345,0.0940218,0.0003946653,0.0001684281,0.0001513115,0.006530209,0.0003332451,0.008583548],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.008477905,"threshold_uncertainty_score":0.01685709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08221847107016066,"score_gpt":0.2703371859817398,"score_spread":0.1881187149115791,"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."}}