{"id":"W4394052197","doi":"10.5281/zenodo.3766139","title":"Geometric renormalization unravels self-similarity of the multiscale human connectome","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Spaceflight effects on biology","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Connectome; Self-similarity; Renormalization; Similarity (geometry); Statistical physics; Functional connectivity; Computer science; Mathematics; Geography; Physics; Artificial intelligence; Psychology; Neuroscience; Geometry; Mathematical physics; Image (mathematics)","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":[0.0008459762,0.002035852,0.001178758,0.002340638,0.0006426209,0.001096982,0.001861149,0.002128777,0.007668682],"category_scores_gemma":[0.002925874,0.0003792912,0.001514272,0.001871336,0.000555919,0.0005866057,0.001578948,0.001120092,0.007032587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009289671,"about_ca_system_score_gemma":0.0009274199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01897301,"about_ca_topic_score_gemma":0.04655478,"domain_scores_codex":[0.9995939,0.00007827434,0.00002314489,0.0001508068,0.00009462285,0.00005934473],"domain_scores_gemma":[0.9993606,0.0002087097,0.00006145688,0.0001866444,0.000100894,0.00008164698],"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":[0.0008427047,0.0002112238,0.01269136,0.002177753,0.0007016387,0.0004406036,0.0001525145,0.009923406,0.002892024,0.002493847,0.939489,0.02798394],"study_design_scores_gemma":[0.003116107,0.0005170497,0.173743,0.001256098,0.0009559465,0.003827445,0.0004752808,0.06437355,0.008271572,0.02749962,0.7156225,0.0003419133],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02858078,0.001762448,0.001970689,0.0006064608,0.0001806747,0.00007163415,0.9608271,0.003560951,0.002439222],"genre_scores_gemma":[0.02231041,0.0003198014,0.002548742,0.0001543766,0.00004861425,0.0001270151,0.9730324,0.0001595349,0.001299053],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01897301,"threshold_uncertainty_score":0.03772515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03621245679705588,"score_gpt":0.2784422408706853,"score_spread":0.2422297840736294,"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."}}