{"id":"W4254987946","doi":"10.4018/978-1-4666-0261-8.ch005","title":"On Visual Semantic Algebra (VSA)","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Visual Objects; Object (grammar); Artificial intelligence; Set (abstract data type); Process (computing); Cognition; Cognitive neuroscience of visual object recognition; Inference; Process calculus; Perception; Cognitive architecture; Visual perception; Cognitive science; Pattern recognition (psychology); Theoretical computer science; Programming language; Psychology","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002115893,0.0005682182,0.0004889845,0.00009726762,0.0001756758,0.0002111307,0.0009727834,0.0004285052,0.0000343281],"category_scores_gemma":[0.0000205988,0.0005577974,0.0002977459,0.00003548248,0.00009124039,0.00006666782,0.000726951,0.0005471435,0.00166729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001688314,"about_ca_system_score_gemma":0.0001350486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001108175,"about_ca_topic_score_gemma":0.00001034181,"domain_scores_codex":[0.9975638,0.00004216513,0.0003545965,0.0007971872,0.0005796654,0.0006625532],"domain_scores_gemma":[0.9984185,0.0001803783,0.0002339796,0.0007332843,0.0001398239,0.0002940375],"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":[0.000008890977,0.0000160232,0.000004256088,0.00001133989,0.00005192187,0.00006250342,0.00002712811,0.000002728776,0.000001174662,0.7886633,0.003818185,0.2073326],"study_design_scores_gemma":[0.0005604862,0.0004558044,0.0001698418,0.0009733145,0.0001005189,0.0001648512,0.000001564435,0.004399698,0.00004774154,0.9548447,0.0369111,0.00137039],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0002504082,0.0007475904,0.03891641,0.00007613637,0.001810331,0.0002492013,0.00001281081,0.0005083172,0.9574288],"genre_scores_gemma":[0.9262255,0.000009720142,0.0009048961,0.002466467,0.001607809,0.000008498559,0.000005013264,0.00006654213,0.06870552],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9259751,"threshold_uncertainty_score":0.9996874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881048598598188,"score_gpt":0.2564302986554235,"score_spread":0.2376198126694417,"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."}}