{"id":"W2951781132","doi":"10.1016/j.neulet.2017.02.064","title":"Cracking the barcode of fullerene-like cortical microcolumns","year":2017,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Neuroscience; Biological neural network; Connectome; Computer science; Artificial neural network; Spiking neural network; Topology (electrical circuits); Nervous system; Nerve net; Biological system; Biology; Artificial intelligence; Mathematics; Functional connectivity; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008364598,0.00008785765,0.00009297799,0.00002117912,0.0005611263,0.00008116581,0.0006326674,0.00002402429,0.000003686408],"category_scores_gemma":[0.000101299,0.0000685733,0.00004275071,0.00005983235,0.0003352711,0.0002064733,0.0001049115,0.0003064337,0.000004375655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009017445,"about_ca_system_score_gemma":0.000004487657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002694108,"about_ca_topic_score_gemma":0.000001844902,"domain_scores_codex":[0.999284,0.00001866795,0.0001334705,0.0001655012,0.0001456093,0.0002527787],"domain_scores_gemma":[0.9994059,0.0000749485,0.0000548192,0.0004128281,0.00000897979,0.00004252988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001777058,0.000002907674,0.0007868462,0.000007927963,5.723944e-7,0.0000110148,0.00004803239,0.02359194,0.9741077,0.00002812948,0.0002806061,0.001132502],"study_design_scores_gemma":[0.0003140306,0.00005382925,0.1183762,0.00005940249,0.00001310107,0.00006212036,0.00003456466,0.06694826,0.8049459,0.00007043694,0.008789983,0.0003321638],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880627,0.000008717605,0.009343449,0.001273169,0.0009105123,0.00008786562,0.000001327877,0.00006901307,0.0002432414],"genre_scores_gemma":[0.9972869,0.000006431657,0.0002022061,0.002402639,0.00006901141,0.000003172358,8.959496e-8,0.00001080981,0.00001877396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1691618,"threshold_uncertainty_score":0.4315787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02586116444394798,"score_gpt":0.2596998657900507,"score_spread":0.2338387013461027,"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."}}