{"id":"W1007063632","doi":"","title":"Dealing with data complexity: on neural networks and fusion in biometric research","year":2010,"lang":"en","type":"article","venue":"Journal of Medical Informatics & Technologies","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Biometrics; Computer science; Artificial neural network; Sensor fusion; Artificial intelligence; Biometric data","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":[0.008948208,0.0008246778,0.001964612,0.001557271,0.0007406729,0.002943666,0.001771354,0.002873371,0.001230516],"category_scores_gemma":[0.02563692,0.0006404879,0.001316029,0.002899607,0.002870936,0.008701704,0.003627766,0.002697183,0.0002213497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001175204,"about_ca_system_score_gemma":0.0007802786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003181806,"about_ca_topic_score_gemma":0.002282623,"domain_scores_codex":[0.9960078,0.001804949,0.0003558419,0.0005246825,0.001059895,0.0002468191],"domain_scores_gemma":[0.9840716,0.01216378,0.0006732078,0.001399625,0.001506285,0.0001855494],"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":[0.0002998214,0.0001683991,0.003457523,0.0004972832,0.0003444764,0.0002043586,0.0005188642,0.3254648,0.00285482,0.2065784,0.002659348,0.4569519],"study_design_scores_gemma":[0.000009671508,0.00005103153,0.0008055541,0.00006560895,0.00006586837,0.0000836812,0.00006492193,0.8302978,0.001322712,0.1656574,0.001536117,0.00003966358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02087295,0.009170854,0.9655186,0.002297484,0.0001796893,0.00003485725,0.00003009239,0.00009168698,0.001803791],"genre_scores_gemma":[0.6819242,0.01484866,0.2962342,0.0006892863,0.001998977,0.0001392657,0.0001081563,0.0001018087,0.003955335],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008948208,"threshold_uncertainty_score":0.04732323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1677678073598637,"score_gpt":0.3931490647114482,"score_spread":0.2253812573515845,"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."}}