{"id":"W2150060182","doi":"10.3389/fncom.2013.00021","title":"Local field potentials reflect multiple spatial scales in V4","year":2013,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Montreal Neurological Institute and Hospital; McGill University","funders":"Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Local field potential; Field (mathematics); Neuroscience; Psychology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007445495,0.000101483,0.000122462,0.0001886435,0.0000398295,0.00005776102,0.0001866334,0.00003518477,0.000008974198],"category_scores_gemma":[0.00009573858,0.0001091595,0.00002670726,0.0003401586,0.00009962499,0.0002178513,0.00002916795,0.000157975,0.0000145555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005033864,"about_ca_system_score_gemma":0.00001726142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001547471,"about_ca_topic_score_gemma":0.00006647781,"domain_scores_codex":[0.9990841,0.0000294621,0.0002068231,0.0002217939,0.0002138363,0.0002439856],"domain_scores_gemma":[0.9997332,0.00009331895,0.0000182653,0.00008441805,0.00002117307,0.00004962576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003662373,0.00002195974,0.0356335,0.000009064014,6.73605e-7,0.00001295185,0.00005252594,0.9423232,0.002127458,0.00002928552,0.004291939,0.01549376],"study_design_scores_gemma":[0.0001978499,0.00001779425,0.1481492,0.00001335306,5.142634e-7,0.000005012976,0.00002795565,0.8483912,0.0005627432,0.002369609,0.0001599781,0.0001047861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3596049,0.00004897644,0.6382948,0.000313904,0.001308025,0.0001222497,0.000002869497,0.00007221755,0.000232057],"genre_scores_gemma":[0.9882761,0.00001040737,0.01124629,0.000393677,0.000028758,0.00001155646,0.000002920824,0.00001068316,0.00001960249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6286712,"threshold_uncertainty_score":0.4451396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007648711472084798,"score_gpt":0.2172204671646094,"score_spread":0.2095717556925246,"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."}}