{"id":"W4211117539","doi":"10.1007/978-1-4471-7452-3_25","title":"Combining Multiple Learners: Data Fusion and Ensemble Learning","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Viewpoints; Brainstorming; Ensemble learning; Computer science; Artificial intelligence; Voting; Majority rule; Machine learning; Domain (mathematical analysis); Training set; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001486773,0.0001879175,0.0002093844,0.00005202582,0.0001747624,0.0002017347,0.0009860616,0.0001356659,0.00004970905],"category_scores_gemma":[0.00001082639,0.0001657695,0.00003081498,0.0000309196,0.00003263123,0.0002952417,0.00207225,0.0004356217,0.0003046464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000878949,"about_ca_system_score_gemma":0.00003323612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001939756,"about_ca_topic_score_gemma":0.00002128699,"domain_scores_codex":[0.9987583,0.00001158273,0.0001771704,0.0007025336,0.0001741233,0.0001762589],"domain_scores_gemma":[0.9984135,0.0002055684,0.0001278223,0.001150327,0.000028728,0.00007407169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002588506,0.00001047859,0.00009397828,0.00002390763,0.0000222758,0.000007367665,0.00008540809,0.0003009223,0.0003337697,0.8120859,0.01443799,0.1725954],"study_design_scores_gemma":[0.0001913071,0.00004800857,0.00001786653,0.00008519352,0.00001004788,0.00001460443,0.00001006875,0.2970525,0.00001705959,0.004135475,0.6981252,0.0002925996],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001494913,0.0006382076,0.194002,0.0009170576,0.0002685426,0.000386916,0.000007836725,0.0003665955,0.8032633],"genre_scores_gemma":[0.04696316,0.0007344222,0.01528403,0.0003808604,0.0001468542,0.000003046609,0.0001801305,0.00003949463,0.936268],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8079504,"threshold_uncertainty_score":0.6759882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05542423212255605,"score_gpt":0.2566458108379175,"score_spread":0.2012215787153615,"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."}}