{"id":"W2000908437","doi":"10.1162/neco.2007.10-06-361","title":"A Principle for Learning Egocentric-Allocentric Transformation","year":2007,"lang":"en","type":"letter","venue":"Neural Computation","topic":"Memory and Neural Mechanisms","field":"Neuroscience","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial intelligence; Orientation (vector space); Computer science; Sensory system; Boltzmann machine; Invariant (physics); Population; Restricted Boltzmann machine; Psychology; Artificial neural network; Computer vision; Neuroscience; Pattern recognition (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001328992,0.0004490367,0.0004595726,0.0005178966,0.000598961,0.001438895,0.001578942,0.001443751,0.004727115],"category_scores_gemma":[0.003745054,0.0004047088,0.0007556843,0.0004191468,0.004921994,0.003236628,0.00154559,0.002503044,0.001673917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009649511,"about_ca_system_score_gemma":0.0007240043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001234588,"about_ca_topic_score_gemma":0.0009919098,"domain_scores_codex":[0.9993524,0.00014652,0.00003530732,0.0002072355,0.0002175632,0.00004100684],"domain_scores_gemma":[0.9993556,0.0002063238,0.00007851852,0.0002114736,0.0001105985,0.00003754508],"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":[0.00003972809,0.00001547632,0.0001923095,0.00005697954,0.00003121105,0.00002949606,0.00008850145,0.01784328,0.002628394,0.9238716,0.002388177,0.05281471],"study_design_scores_gemma":[0.00002646257,0.00003858386,0.0002023857,0.00001796739,0.000007454741,0.000089622,0.000009707656,0.06064767,0.001413478,0.9283246,0.009204859,0.00001726281],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00562777,0.0004095872,0.9746241,0.001939081,0.0001241297,0.00005297544,0.00007685405,0.0003193482,0.01682624],"genre_scores_gemma":[0.4518283,0.001090545,0.5226574,0.001868413,0.0004623574,0.0006489281,0.0002432873,0.0003411858,0.02085964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004727115,"threshold_uncertainty_score":0.01581383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1115410951714591,"score_gpt":0.3487772375335175,"score_spread":0.2372361423620585,"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."}}