{"id":"W2593484808","doi":"10.1016/j.neucom.2017.02.080","title":"Editorial learning for multimodal data","year":2017,"lang":"en","type":"article","venue":"Neurocomputing","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Scheme (mathematics); Process (computing); Data mining; Information retrieval; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002632415,0.001584054,0.001607149,0.002191789,0.001501535,0.003667242,0.001844619,0.006100738,0.02191844],"category_scores_gemma":[0.02176652,0.0005205813,0.001339599,0.0008380286,0.001575463,0.00298464,0.001254369,0.008477247,0.008184298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008565268,"about_ca_system_score_gemma":0.0009744694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004733264,"about_ca_topic_score_gemma":0.0008864994,"domain_scores_codex":[0.9982691,0.0003079618,0.0002094371,0.0003739093,0.0007187337,0.0001208317],"domain_scores_gemma":[0.9809008,0.01090481,0.0007924156,0.0006086814,0.005462493,0.001330667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003372564,0.00001013116,0.00003581113,0.0002507796,0.00002251347,0.0001220342,0.000007552729,0.0000452104,0.000118751,0.0007049908,0.9830839,0.01556458],"study_design_scores_gemma":[0.00004548182,0.00004535534,0.0002932737,0.0003691197,0.00005378478,0.0006484452,0.0000270468,0.0007369745,0.0003873997,0.004852016,0.992514,0.00002712047],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"empirical","genre_scores_codex":[0.0001084009,0.004623104,0.001453573,0.03937478,0.9524463,0.00001779671,0.0001115488,0.0001438455,0.001720568],"genre_scores_gemma":[0.001643557,0.003002505,0.0007947064,0.01595287,0.9691937,0.00003502161,0.00006072582,0.00008716891,0.009229788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02191844,"threshold_uncertainty_score":0.0733245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06019089979481864,"score_gpt":0.3447580023664258,"score_spread":0.2845671025716072,"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."}}