{"id":"W3042292785","doi":"10.1016/j.tics.2020.06.006","title":"The Face of Image Reconstruction: Progress, Pitfalls, Prospects","year":2020,"lang":"en","type":"review","venue":"Trends in Cognitive Sciences","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Baycrest Hospital; The Scarborough Hospital; University of Toronto","funders":"National Eye Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Face (sociological concept); Psychology; Facial recognition system; Cognitive science; Face perception; Cognitive psychology; Artificial intelligence; Computer science; Pattern recognition (psychology); Neuroscience; Perception; Sociology","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":[0.002674472,0.001140526,0.002255877,0.002190572,0.0004628278,0.002692215,0.002068433,0.003005979,0.005219417],"category_scores_gemma":[0.003821304,0.0004162443,0.0006336881,0.002000661,0.002172893,0.004516819,0.001415929,0.004103683,0.003105995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001146135,"about_ca_system_score_gemma":0.002039184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001906013,"about_ca_topic_score_gemma":0.003353852,"domain_scores_codex":[0.9996262,0.0001045385,0.00004468839,0.00006618046,0.0001203014,0.0000380305],"domain_scores_gemma":[0.9976708,0.001554003,0.000140859,0.00007047313,0.0004142694,0.0001496116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000115182,0.00005089231,0.0001448571,0.009852841,0.0000829732,0.0001297614,0.00006899599,0.0003872467,0.0006042562,0.01358572,0.03920105,0.9357764],"study_design_scores_gemma":[0.00002784142,0.00007640625,0.0005426689,0.007157672,0.000121477,0.001166748,0.0001208371,0.0002807409,0.0003428542,0.0167769,0.9733418,0.00004409841],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000290229,0.9986398,0.0001851131,0.0005615008,0.0002202532,0.000001567822,0.00000625741,0.000005669252,0.000350918],"genre_scores_gemma":[0.000437028,0.9980332,0.0003350725,0.0004131847,0.0005468361,0.000004341758,0.00001232055,0.00000290215,0.0002151539],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005219417,"threshold_uncertainty_score":0.0174607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2892247421083901,"score_gpt":0.4597204333898263,"score_spread":0.1704956912814362,"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."}}