{"id":"W4379387303","doi":"10.1101/2023.05.31.543092","title":"<tt>conn2res</tt> : A toolbox for connectome-based reservoir computing","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital","funders":"","keywords":"Computer science; Connectomics; Connectome; Toolbox; Reservoir computing; Computational neuroscience; Artificial intelligence; Python (programming language); Network dynamics; Spiking neural network; Artificial neural network; Biological neural network; Neuromorphic engineering; Theoretical computer science; Neuroscience; Machine learning; Recurrent neural network; Functional connectivity","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":[0.001133237,0.001726274,0.0009213471,0.001450102,0.0007719683,0.00219305,0.003299203,0.001650195,0.09517694],"category_scores_gemma":[0.004251974,0.0009818703,0.001527654,0.001174047,0.001031625,0.00276294,0.003345496,0.003369681,0.0339913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006807733,"about_ca_system_score_gemma":0.001634555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001946704,"about_ca_topic_score_gemma":0.004070526,"domain_scores_codex":[0.9994733,0.0001042108,0.00005028576,0.0001066687,0.0001936229,0.00007199196],"domain_scores_gemma":[0.9988561,0.0004785283,0.0001074571,0.0002295335,0.0001920965,0.0001363603],"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":[0.000614447,0.000118361,0.002303343,0.002273925,0.000268185,0.001296677,0.0005431644,0.03014471,0.02258196,0.1311569,0.6521204,0.1565779],"study_design_scores_gemma":[0.0004007009,0.00007171829,0.002066287,0.0004067262,0.00006503984,0.001217359,0.00006966565,0.2280121,0.03566097,0.1423247,0.5894865,0.0002182505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.004480577,0.0005064324,0.6465808,0.001002543,0.0004736531,0.0001547936,0.02674358,0.3040364,0.0160212],"genre_scores_gemma":[0.112271,0.001984853,0.598354,0.002307443,0.0004629269,0.002389489,0.0539571,0.183944,0.04432911],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.09517694,"threshold_uncertainty_score":0.3183986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05251788116717317,"score_gpt":0.2632791324079902,"score_spread":0.210761251240817,"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."}}