{"id":"W4409793571","doi":"10.61091/jcmcc127a-247","title":"Optimization and application of image recognition algorithm based on DouN-GNN model in two-node graph neural network","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial neural network; Image (mathematics); Algorithm; Node (physics); Artificial intelligence; Pattern recognition (psychology); Graph; Theoretical computer science; Engineering","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":[0.0006321293,0.001000994,0.0009060204,0.0007372525,0.000492621,0.0008941163,0.001561298,0.001242895,0.001700585],"category_scores_gemma":[0.001515098,0.000396189,0.0007054281,0.0006892853,0.0007029785,0.00127486,0.0008846094,0.00112817,0.0003753609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001459921,"about_ca_system_score_gemma":0.00130447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02050097,"about_ca_topic_score_gemma":0.015191,"domain_scores_codex":[0.9996338,0.00006124908,0.00002074726,0.0001298785,0.0000919177,0.00006242067],"domain_scores_gemma":[0.9996608,0.0001205289,0.00003565181,0.00003106886,0.0001306311,0.00002131927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005398596,0.0000377638,0.0009417744,0.00005743505,0.00003607931,0.00005703788,0.00004490921,0.9111189,0.002643325,0.005526499,0.001188046,0.07829422],"study_design_scores_gemma":[0.000002362196,0.000009119188,0.00006214415,0.000001665562,0.000003543189,0.00000798081,0.000003706579,0.9984548,0.000370828,0.0009445135,0.000136594,0.0000027682],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02980443,0.000449403,0.9641956,0.0003560861,0.0000852115,0.00007670576,0.0000563892,0.000818569,0.00415747],"genre_scores_gemma":[0.7702425,0.0004867981,0.2210898,0.0003487764,0.0000448267,0.0002748368,0.0003048838,0.0001687915,0.007038799],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02050097,"threshold_uncertainty_score":0.04076332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0174088489778431,"score_gpt":0.270321290995609,"score_spread":0.2529124420177659,"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."}}