{"id":"W2735976292","doi":"10.1101/164954","title":"Neural network models of the tactile system develop first-order units with spatially complex receptive fields","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Actua; Western University","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Receptive field; Computer science; Artificial neural network; Noise (video); Artificial intelligence; Complex system; Order (exchange); Field (mathematics); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000548935,0.0003510447,0.000389725,0.0002855245,0.0002605683,0.00100584,0.0006326287,0.001255864,0.002033278],"category_scores_gemma":[0.002270312,0.000436551,0.0004561939,0.0002375136,0.0008839782,0.001804612,0.0005834633,0.0008270702,0.0003718857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007197816,"about_ca_system_score_gemma":0.0004005345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002740985,"about_ca_topic_score_gemma":0.00340518,"domain_scores_codex":[0.9998809,0.00003632535,0.00000392739,0.00003012569,0.00002535599,0.00002327746],"domain_scores_gemma":[0.9992698,0.0003727098,0.0001205185,0.00007386733,0.00008058108,0.00008254913],"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":[0.000028431,0.00002440582,0.001024812,0.00003647299,0.00002309659,0.0000853325,0.00008724737,0.9357083,0.007796746,0.05071589,0.000816113,0.003653052],"study_design_scores_gemma":[0.000003330443,0.000004012997,0.0002967513,0.000002462793,0.000001275963,0.00001094953,0.000004577801,0.9836113,0.000237196,0.01573761,0.00008775157,0.000002835658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5273744,0.0005307434,0.4526111,0.001969079,0.00006112907,0.00002857158,0.0001311806,0.0003593941,0.01693437],"genre_scores_gemma":[0.9831463,0.0001716993,0.01249017,0.00008800711,0.0000169647,0.00002568939,0.0000300665,0.00003995841,0.003991088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002740985,"threshold_uncertainty_score":0.006801963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04301624024107136,"score_gpt":0.2211198424442115,"score_spread":0.1781036022031402,"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."}}