{"id":"W2045435736","doi":"10.12688/f1000research.2-19.v1","title":"Moving beyond Type I and Type II neuron types","year":2013,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neuroscience; Terminology; Context (archaeology); Type (biology); Cognitive science; Computer science; Cell type; Synchronization (alternating current); Computational neuroscience; Psychology; Biology","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":[0.002969612,0.0009226631,0.001384435,0.00122827,0.001332641,0.004248864,0.002381802,0.002899864,0.00580234],"category_scores_gemma":[0.005062693,0.0005188534,0.001666714,0.0006455972,0.006403345,0.01085295,0.002915648,0.009848401,0.002849969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002479997,"about_ca_system_score_gemma":0.001804685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004067736,"about_ca_topic_score_gemma":0.002646183,"domain_scores_codex":[0.9984268,0.0002811972,0.0001171009,0.0005939065,0.0004028455,0.0001781569],"domain_scores_gemma":[0.9972298,0.0007790225,0.000317507,0.0005960827,0.0007137322,0.0003638802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001087252,0.00002636797,0.003173358,0.0003517433,0.00005507992,0.0001405732,0.001056531,0.001577171,0.004249477,0.9169108,0.01614038,0.0562098],"study_design_scores_gemma":[0.00001457352,0.00006820268,0.001431263,0.0002609743,0.0000387369,0.0004312861,0.0003273282,0.004100832,0.001183094,0.8887354,0.1033608,0.00004739423],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05149403,0.08335464,0.5665994,0.1333278,0.01975215,0.0001474044,0.001326006,0.000894016,0.1431046],"genre_scores_gemma":[0.5998414,0.0571327,0.2171143,0.04489917,0.01129101,0.0005724572,0.0009271185,0.000783762,0.06743815],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00580234,"threshold_uncertainty_score":0.01941073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06877723936525924,"score_gpt":0.3269487131094523,"score_spread":0.258171473744193,"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."}}