{"id":"W1592572528","doi":"10.1007/3-540-29344-2_28","title":"A Study of Orientation Selectivity of TAM Network Incorporated Receptive Field Structure","year":2005,"lang":"en","type":"book-chapter","venue":"","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Receptive field; Orientation (vector space); Feature (linguistics); Character (mathematics); Artificial intelligence; Pattern recognition (psychology); Computer science; Field (mathematics); Artificial neural network; Function (biology); Computer vision; Mathematics; Geometry; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006800557,0.0001731877,0.0001483267,0.0002211845,0.0001322657,0.0002123858,0.0002972486,0.0001667351,0.001958553],"category_scores_gemma":[0.0001634218,0.00009611928,0.0002192126,0.0001957827,0.0002168209,0.0005323539,0.0001256049,0.0002675581,0.0002551492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002312053,"about_ca_system_score_gemma":0.00009847994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006643502,"about_ca_topic_score_gemma":0.0006337364,"domain_scores_codex":[0.999981,0.000002168141,4.908275e-7,0.000007335238,0.000004068818,0.000004866715],"domain_scores_gemma":[0.9999474,0.00002558587,0.000003937394,0.000006822739,0.00001016979,0.000006096018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001586328,0.00005384699,0.002124522,0.0002666106,0.00004225628,0.0005208543,0.0002163337,0.01570018,0.6745025,0.1831219,0.002446129,0.1208462],"study_design_scores_gemma":[0.00001903848,0.0002390548,0.0205247,0.00003434042,0.0000788137,0.001872214,0.0002096436,0.4766082,0.3369451,0.1455025,0.01791675,0.00004966425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5290579,0.00312051,0.3997354,0.0002065711,0.000187526,0.00005133431,0.0002491686,0.0004807306,0.06691092],"genre_scores_gemma":[0.9511322,0.0008367695,0.03284679,0.00004679607,0.00003941849,0.00001737295,0.00009133227,0.00006634964,0.01492297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001958553,"threshold_uncertainty_score":0.006551981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05875995470876021,"score_gpt":0.3190027111185955,"score_spread":0.2602427564098353,"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."}}