{"id":"W7144331872","doi":"10.71465/ajainn620","title":"Enhancing AI Models with Data Fusion Techniques","year":2023,"lang":"","type":"article","venue":"American Journal of Artificial Intelligence and Neural Networks","topic":"Artificial Intelligence Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Sensor fusion; Fusion; Data modeling; Data type; Data integration; Field (mathematics); Big 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002125744,0.0005571598,0.0009297405,0.0006284335,0.0007418696,0.0007760709,0.003214695,0.0001575507,0.00002783],"category_scores_gemma":[0.0001206804,0.000466064,0.000160225,0.004470962,0.00164196,0.00302967,0.001422025,0.001327361,0.0000348567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006338073,"about_ca_system_score_gemma":0.0002876857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002514909,"about_ca_topic_score_gemma":0.0003045499,"domain_scores_codex":[0.9945515,0.0003302635,0.00208652,0.001080654,0.0008927117,0.001058348],"domain_scores_gemma":[0.9945543,0.000745313,0.001666095,0.001619962,0.0008582923,0.0005560552],"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":[0.0002272773,0.0001154295,0.00005186232,0.00001069168,0.0000680856,0.0001303041,0.001262141,0.1055136,0.000850886,0.008198753,0.000338984,0.883232],"study_design_scores_gemma":[0.00001718326,0.002190898,0.00002026489,0.0002991905,0.000101657,0.0003001069,0.002760116,0.964862,0.01536628,0.01322088,0.0003423286,0.0005190358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03534678,0.0005938613,0.9569542,0.005900461,0.0005831841,0.0004121178,0.00001412271,0.0001523106,0.00004295203],"genre_scores_gemma":[0.9772298,0.005009205,0.01538716,0.001139103,0.00112347,0.00001173691,0.00001227508,0.00005794814,0.00002928135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.941883,"threshold_uncertainty_score":0.9997791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08533505248020795,"score_gpt":0.3389046031550145,"score_spread":0.2535695506748065,"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."}}