{"id":"W2895271043","doi":"10.3791/58116","title":"Analyzing the Size, Shape, and Directionality of Networks of Coupled Astrocytes","year":2018,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Neuroscience and Neuropharmacology Research","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Neuroscience; Coupling (piping); Gap junction; Nucleus; Computer science; Directionality; Physics; Biological system; Network analysis; Astrocyte; Nerve net; Orientation (vector space); Biology; Topology (electrical circuits); Materials science; Cell biology; Mathematics; Central nervous system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004199885,0.0001934637,0.0002024359,0.0007642199,0.0002357867,0.0005293382,0.0003083184,0.000339584,0.0008651728],"category_scores_gemma":[0.002135202,0.0003019255,0.0002815253,0.0004817643,0.000311074,0.0006639792,0.0004683116,0.000318828,0.0002176843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003513912,"about_ca_system_score_gemma":0.0003081794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002924674,"about_ca_topic_score_gemma":0.004365351,"domain_scores_codex":[0.999873,0.00002727115,0.000006945598,0.0000385848,0.00003262016,0.00002151565],"domain_scores_gemma":[0.9990367,0.000378615,0.0002235659,0.00007946197,0.0001504309,0.0001312753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008290506,0.0001103949,0.09707268,0.0004358207,0.0003495673,0.0007891397,0.00117734,0.2058859,0.5530865,0.01422119,0.004553875,0.1214886],"study_design_scores_gemma":[0.00004872654,0.0001793051,0.1107795,0.00004919533,0.0001301221,0.0007416696,0.0006751617,0.81881,0.04536742,0.02013901,0.002997919,0.00008200039],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8967533,0.0005069572,0.09881096,0.000183339,0.00003842012,0.00002578554,0.0003570482,0.0003375682,0.002986756],"genre_scores_gemma":[0.9700723,0.0003154354,0.02793458,0.00004414246,0.00002123889,0.00002392591,0.0003473822,0.00007389314,0.00116708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002924674,"threshold_uncertainty_score":0.005815327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07019960308660993,"score_gpt":0.4723484861882271,"score_spread":0.4021488831016172,"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."}}