{"id":"W7132948642","doi":"","title":"Analysis of electrical activities in hippocampal slices using coherence measures","year":2005,"lang":"","type":"dissertation","venue":"TSpace","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Coherence (philosophical gambling strategy); Hippocampal formation; SIGNAL (programming language); Signal processing; Wavelet; Pattern recognition (psychology); Wavelet transform","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001230241,0.0005576857,0.001380853,0.003173066,0.0001417495,0.0003109701,0.001278148,0.0006068934,0.0001456924],"category_scores_gemma":[0.0001906526,0.0006259246,0.000454064,0.00695549,0.0001341949,0.0007808206,0.0001074638,0.0008281007,0.000004320531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003187434,"about_ca_system_score_gemma":0.0009487978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002189803,"about_ca_topic_score_gemma":0.005702325,"domain_scores_codex":[0.9953987,0.0007691407,0.001033736,0.0009711891,0.001247795,0.0005794258],"domain_scores_gemma":[0.9968843,0.0004668435,0.001284723,0.0008437624,0.0003906071,0.0001297637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008834374,0.002431083,0.05657368,0.0004546607,0.004819312,0.00004402555,0.4876372,0.09402832,0.1391846,0.02296546,0.0001505166,0.1908278],"study_design_scores_gemma":[0.0004649937,0.0003512715,0.04952021,0.0004154352,0.001564605,0.000005007982,0.009137539,0.8069241,0.1296887,0.000401345,0.0002116253,0.00131517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8887064,0.00110764,0.1068153,0.0001000559,0.0001283883,0.0004634067,0.000004824719,0.0001252632,0.002548673],"genre_scores_gemma":[0.9764017,0.0002450314,0.02227217,0.0000800622,0.0000557732,0.00003475589,0.00004469436,0.00002929305,0.0008364754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7128958,"threshold_uncertainty_score":0.9996192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04618058818482126,"score_gpt":0.3766886972671009,"score_spread":0.3305081090822797,"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."}}