{"id":"W1997502120","doi":"10.1109/icci-cc.2013.6622228","title":"Novel multimodal template generation algorithm","year":2013,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Biometrics; Computer science; Artificial intelligence; Pattern recognition (psychology); Feature extraction; Random projection; Context (archaeology); Data mining; Algorithm","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":[0.0001139345,0.00005342643,0.00004862833,0.0001389413,0.00008129164,0.0003093064,0.0003233731,0.000040286,0.0002808344],"category_scores_gemma":[0.00001351115,0.00004508525,0.00002477251,0.0005209308,0.00001314773,0.0005818081,0.00007140396,0.0000433801,0.001107017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001645879,"about_ca_system_score_gemma":0.00001712172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005413208,"about_ca_topic_score_gemma":0.000007764546,"domain_scores_codex":[0.9993836,0.00001228776,0.0001275986,0.0002034134,0.0001579421,0.0001151169],"domain_scores_gemma":[0.9994983,0.000013874,0.00003124125,0.0002783964,0.0001159892,0.00006216679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[4.687213e-8,0.0001011775,0.00004485768,0.000001508475,0.000006203168,4.028358e-7,0.000159694,0.000006101227,0.04275629,0.02137523,0.0232758,0.9122727],"study_design_scores_gemma":[0.0001473939,0.000007128778,0.005253884,3.822927e-7,5.661753e-7,0.000006036315,0.000005132221,0.9775775,0.007141403,0.0002169079,0.009560924,0.00008274626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002921633,0.00001302569,0.9934768,0.001237076,0.0004120601,0.0001127766,0.000001224098,0.0001325716,0.001692816],"genre_scores_gemma":[0.252382,0.000003388705,0.7433163,0.0006451213,0.00008409924,0.00001949238,0.00000937215,0.000002884037,0.003537372],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9775714,"threshold_uncertainty_score":0.9996707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03597555625933514,"score_gpt":0.2506411379798987,"score_spread":0.2146655817205636,"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."}}