{"id":"W2043630098","doi":"10.1145/1413634.1413668","title":"Biometric tendency recognition and classification system","year":2008,"lang":"en","type":"article","venue":"","topic":"Aesthetic Perception and Analysis","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Biometrics; Computer science; Relation (database); Context (archaeology); Biometric data; Software; Contextual image classification; Statistical classification; Artificial intelligence; Computer security; Pattern recognition (psychology); Image (mathematics); Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00005671043,0.00004403605,0.00005697277,0.0002605511,0.000132972,0.0000141048,0.00004057448,0.00002788696,0.000190338],"category_scores_gemma":[0.00006674421,0.00003475239,0.00002346941,0.0007498949,0.00006312458,0.00008965766,0.00000919173,0.00003029284,0.0009628832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001955453,"about_ca_system_score_gemma":0.000006851554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009614585,"about_ca_topic_score_gemma":5.258822e-7,"domain_scores_codex":[0.9994772,0.00004198173,0.0001027226,0.0001803204,0.0001269817,0.00007079588],"domain_scores_gemma":[0.9998021,0.00001229783,0.00003428684,0.00008465874,0.00002034,0.00004628454],"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":[0.000007683254,0.000112075,0.003389933,0.00002462921,0.00000135896,0.00001564275,0.0003240695,4.382143e-7,0.8518088,0.003823394,0.001027569,0.1394644],"study_design_scores_gemma":[0.003906547,0.000719063,0.6472688,0.0001602077,0.0002395484,0.007601925,0.0117073,0.1110229,0.1911241,0.002237655,0.02158271,0.002429317],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9516951,0.00001049973,0.003038508,0.0002167934,0.00003301371,0.0000505949,0.000003090704,0.0001355972,0.04481676],"genre_scores_gemma":[0.9976509,0.0001963807,0.0001999257,0.0001700396,0.00001490011,0.000005180395,0.000002688796,0.000003316386,0.0017567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6606848,"threshold_uncertainty_score":0.999815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1927884471915483,"score_gpt":0.2843481124252893,"score_spread":0.09155966523374101,"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."}}