{"id":"W2172495089","doi":"","title":"Probabilistic Linear Discriminant Analysis for Inferences About Identity.","year":2007,"lang":"en","type":"other","venue":"UCL Discovery (University College London)","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Facial recognition system; Artificial intelligence; Linear discriminant analysis; Face (sociological concept); Computer science; Identity (music); Pattern recognition (psychology); Probabilistic logic; Three-dimensional face recognition; Noise (video); Variation (astronomy); Generative model; Computer vision; Position (finance); Generative grammar; Machine learning; Face detection; Image (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":[0.004315165,0.001954023,0.001790511,0.003005301,0.000844788,0.001904768,0.002468674,0.00188429,0.02102653],"category_scores_gemma":[0.01112556,0.0005987592,0.00106792,0.003766369,0.001328817,0.001785039,0.002578219,0.002685396,0.01991988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009560225,"about_ca_system_score_gemma":0.0008876789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00208446,"about_ca_topic_score_gemma":0.002706478,"domain_scores_codex":[0.9974164,0.001121953,0.0001194653,0.0004834119,0.0007736424,0.00008504384],"domain_scores_gemma":[0.9968333,0.001612046,0.000201576,0.0008641409,0.0003972147,0.00009180506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000959333,0.0001089881,0.001321253,0.0004217158,0.0002023102,0.0001472967,0.0001080198,0.02922427,0.001240179,0.09700955,0.07415581,0.7959647],"study_design_scores_gemma":[0.00005853702,0.00005393794,0.00184499,0.0001553562,0.00006993047,0.000399936,0.00008104947,0.3784116,0.002346578,0.5045727,0.1119329,0.00007257036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00144601,0.01061892,0.9718838,0.00125474,0.0004636557,0.00009547942,0.0014132,0.002589556,0.01023465],"genre_scores_gemma":[0.1096812,0.009494334,0.8404431,0.000852341,0.001500127,0.000740569,0.006139416,0.0008024306,0.03034647],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02102653,"threshold_uncertainty_score":0.07034075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01916790911265012,"score_gpt":0.2461209795798805,"score_spread":0.2269530704672303,"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."}}