{"id":"W2121332993","doi":"10.3758/mc.36.6.1182","title":"Why are some people’s names easier to learn than others? The effects of face similarity on memory for face-name associations","year":2008,"lang":"en","type":"article","venue":"Memory & Cognition","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"National Eye Institute; National Institute of Mental Health","keywords":"Psychology; Similarity (geometry); Recall; Associative property; Face (sociological concept); Content-addressable memory; Set (abstract data type); Cognitive psychology; Association (psychology); Recognition memory; Cognition; Artificial intelligence; Computer science; Neuroscience; Linguistics; Mathematics","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":[0.002248553,0.0003629475,0.0005767456,0.0003919879,0.000377075,0.00162754,0.0007666551,0.001203637,0.007377829],"category_scores_gemma":[0.01850833,0.0004972739,0.0005065208,0.0002978622,0.001231667,0.006668022,0.001007492,0.001351435,0.001028913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002765094,"about_ca_system_score_gemma":0.0002889938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001262114,"about_ca_topic_score_gemma":0.001698849,"domain_scores_codex":[0.9990659,0.0002177487,0.00007557572,0.0003197233,0.0002267448,0.00009421333],"domain_scores_gemma":[0.9885814,0.005524638,0.002553642,0.001709209,0.0007644895,0.0008666491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.02775348,0.00262525,0.2910668,0.001117073,0.001433106,0.001168394,0.008433346,0.001339126,0.4002498,0.005385944,0.006148701,0.2532791],"study_design_scores_gemma":[0.0007329616,0.003098951,0.9276313,0.00008553386,0.0004999689,0.001565037,0.003494644,0.00315112,0.03459056,0.0215463,0.003455891,0.0001476959],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950418,0.00037067,0.0006814014,0.0004725625,0.00009412441,0.00001062579,0.00007298085,0.00001986774,0.003235777],"genre_scores_gemma":[0.9964888,0.0002834066,0.0008689962,0.0003181224,0.00007238479,0.00001051775,0.0001366048,0.0000396375,0.001781615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007377829,"threshold_uncertainty_score":0.02468133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05400950752174472,"score_gpt":0.2894945103855971,"score_spread":0.2354850028638524,"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."}}