{"id":"W7117369618","doi":"10.1016/j.inffus.2025.104103","title":"Deep learning-based astronomical multimodal data fusion: A comprehensive review","year":2025,"lang":"en","type":"article","venue":"Information Fusion","topic":"Gamma-ray bursts and supernovae","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Northern Alberta Development Council; National Key Research and Development Program of China; National Astronomical Observatories, Chinese Academy of Sciences; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Process (computing); Sensor fusion; Field (mathematics); Observational astronomy; Data collection; Emerging technologies; Observational study","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001525661,0.0001546145,0.0002205145,0.00009135019,0.0002091734,0.00007729085,0.0003384041,0.00004546281,0.001503421],"category_scores_gemma":[0.00001848482,0.0001352965,0.00007698357,0.0001809663,0.00003329178,0.0006589583,0.0002868955,0.0002355049,0.0004240439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002585064,"about_ca_system_score_gemma":0.00009286808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001222488,"about_ca_topic_score_gemma":0.000002031958,"domain_scores_codex":[0.9989895,0.00004899718,0.0004378951,0.0001617778,0.0001709861,0.0001908522],"domain_scores_gemma":[0.9991244,0.0000612199,0.0001336876,0.0004579914,0.0001596509,0.00006301412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007305586,0.0001344187,0.09291732,0.0005751086,0.00005990131,5.054494e-7,0.0002230538,0.006119926,0.0001052937,0.0006976495,0.02740357,0.8716902],"study_design_scores_gemma":[0.001004171,0.00003092283,0.03747345,0.0005108733,0.00003882463,2.625789e-7,0.0002561896,0.1543567,0.00006310586,0.00001772929,0.8060699,0.0001778887],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5913225,0.002877119,0.3668109,0.005992683,0.001104187,0.00202558,0.000235091,0.0003138184,0.02931806],"genre_scores_gemma":[0.9893365,0.0001151525,0.002733323,0.001662151,0.0001389324,0.00003585945,0.005684926,0.000009831674,0.0002833497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8715123,"threshold_uncertainty_score":0.9994093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01596632946120218,"score_gpt":0.2672921357206698,"score_spread":0.2513258062594677,"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."}}