{"id":"W2050123757","doi":"10.1109/ijcnn.2011.6033482","title":"Modeling prosopagnosia using dynamic artificial neural networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Artificial neural network; Artificial intelligence","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":[0.000386506,0.0006755927,0.0006193607,0.0006027987,0.0003332632,0.0007984001,0.0009408582,0.001222549,0.001450844],"category_scores_gemma":[0.001572152,0.0005178739,0.0006305048,0.0004115141,0.0004740251,0.0007110284,0.0005280549,0.0006193355,0.0001837776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009397334,"about_ca_system_score_gemma":0.0006146444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01276717,"about_ca_topic_score_gemma":0.0102523,"domain_scores_codex":[0.9998736,0.00003818461,0.000007455723,0.00002640658,0.00002860746,0.0000256875],"domain_scores_gemma":[0.9994673,0.0003523846,0.00006643627,0.00002015536,0.00007041007,0.00002326433],"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":[0.00001074242,0.000008606994,0.0002269187,0.00000576007,0.000008497517,0.00001409401,0.000006122879,0.997669,0.0002743871,0.0006893658,0.00003354279,0.001052935],"study_design_scores_gemma":[0.000001056573,0.000002259114,0.00003326104,6.974217e-7,0.000001272204,0.000001968627,0.000001360425,0.9994996,0.00004298129,0.0003781558,0.00003652788,9.847479e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4531741,0.0009188562,0.5262359,0.0006625052,0.0001195221,0.0001213152,0.0004116618,0.0005374525,0.01781865],"genre_scores_gemma":[0.96105,0.0003929755,0.03339717,0.00006519467,0.00002169889,0.0002279653,0.0002121754,0.00004153577,0.004591191],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01276717,"threshold_uncertainty_score":0.02538568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2125975313110303,"score_gpt":0.3170064470703532,"score_spread":0.104408915759323,"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."}}