{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004130768,0.001359657,0.001497882,0.001489106,0.0006054228,0.002737842,0.002078796,0.00166782,0.002025883],"category_scores_gemma":[0.01651281,0.000665681,0.001504523,0.001989912,0.001089089,0.005216576,0.003349145,0.00288207,0.0008452011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001239079,"about_ca_system_score_gemma":0.001415072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004465626,"about_ca_topic_score_gemma":0.003155638,"domain_scores_codex":[0.9977537,0.0008281,0.0002015844,0.0003319289,0.0007753483,0.0001092614],"domain_scores_gemma":[0.9939647,0.003443317,0.0005054035,0.0008985992,0.001078067,0.0001100067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007295007,0.00007696859,0.0008037855,0.0001590883,0.0001519133,0.00007068082,0.0001697336,0.8552488,0.002484668,0.04603631,0.00163413,0.09309091],"study_design_scores_gemma":[0.000006523307,0.00001779076,0.00006016964,0.00001336561,0.0000183233,0.00001884615,0.00001521864,0.9725158,0.0007605499,0.02526345,0.001301335,0.000008716912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004731091,0.0005340955,0.9917526,0.0005749835,0.00006263451,0.0000518215,0.0000637331,0.0003336949,0.001895378],"genre_scores_gemma":[0.4540375,0.002144456,0.5393663,0.0006132701,0.0002653608,0.000374544,0.0004452582,0.0001575006,0.002595805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004465626,"threshold_uncertainty_score":0.02184582,"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."}}