{"id":"W4229458823","doi":"10.18280/ts.390202","title":"MAF-DeepLab: A Multiscale Attention Fusion Network for Semantic Segmentation","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Jimei University; Natural Science Foundation of Fujian Province","keywords":"Fusion; Segmentation; Computer science; Artificial intelligence; Natural language processing; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005228823,0.001635861,0.0009569429,0.001118061,0.0004127513,0.000677102,0.001615265,0.001239699,0.003480592],"category_scores_gemma":[0.001077298,0.0004566216,0.001068902,0.0007684328,0.0005067347,0.001700643,0.001356893,0.001271455,0.0008232268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001370541,"about_ca_system_score_gemma":0.0009306445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00991963,"about_ca_topic_score_gemma":0.01505527,"domain_scores_codex":[0.9997589,0.00002786479,0.000009060558,0.0001022252,0.00004819372,0.00005374686],"domain_scores_gemma":[0.9998116,0.00004823585,0.00002301451,0.00003232856,0.00005726582,0.00002769078],"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":[0.0004739987,0.0003595618,0.002337227,0.0002697063,0.000335256,0.000248771,0.0001734172,0.1752993,0.06042564,0.01032036,0.02027165,0.7294852],"study_design_scores_gemma":[0.00001897531,0.0001080347,0.0007542283,0.00001659445,0.00005187174,0.00006830745,0.00001892643,0.9772013,0.01040514,0.008566106,0.002772746,0.00001771826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07158101,0.002066866,0.9069865,0.0005198814,0.00020035,0.0001371388,0.001197876,0.0118057,0.005504792],"genre_scores_gemma":[0.7096637,0.0006925447,0.2761561,0.0007970668,0.0001249005,0.0002167054,0.003237274,0.0005268263,0.008584859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00991963,"threshold_uncertainty_score":0.01972383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0368523301076033,"score_gpt":0.2653753529012157,"score_spread":0.2285230227936124,"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."}}