{"id":"W2050270680","doi":"10.1186/1471-2202-8-s2-p72","title":"Principal dynamic mode analysis of hippocampal neuronal networks","year":2007,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Hippocampal formation; Neuroscience; Neuron; Hippocampus; Pyramidal cell; Computer science; Principal component analysis; Pattern recognition (psychology); Artificial intelligence; Biology","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":[0.0002459067,0.000329538,0.0001837033,0.0004340837,0.0001240367,0.0002808149,0.0002673813,0.0001889797,0.0008396815],"category_scores_gemma":[0.001054687,0.0001569125,0.0002912401,0.0003133971,0.0002087015,0.0003639521,0.0002131103,0.0003508805,0.0001576724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001803213,"about_ca_system_score_gemma":0.0002232079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001559154,"about_ca_topic_score_gemma":0.001087498,"domain_scores_codex":[0.9999183,0.00002076245,0.000002779978,0.00002096458,0.00002618891,0.00001097238],"domain_scores_gemma":[0.9998031,0.00009560497,0.00002538692,0.00002323622,0.00004149136,0.00001118533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001276501,0.00003580293,0.002771489,0.0001106759,0.00006299715,0.0001423893,0.0001673205,0.7904568,0.06004274,0.02764298,0.00101599,0.1174231],"study_design_scores_gemma":[0.00000150676,0.00001019416,0.001234875,0.00000250751,0.000002580587,0.00002518318,0.000008838381,0.9906816,0.00186391,0.005808643,0.0003548255,0.000005303699],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1679618,0.0002133516,0.8296673,0.00008004393,0.00001195837,0.00002923021,0.0002293101,0.0002267571,0.001580078],"genre_scores_gemma":[0.915162,0.0003659684,0.08163586,0.00001358218,0.00001141372,0.00007048458,0.0002604844,0.00005107077,0.002429109],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001559154,"threshold_uncertainty_score":0.003100097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02139608065449174,"score_gpt":0.2985163336529,"score_spread":0.2771202529984083,"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."}}