{"id":"W4312641908","doi":"10.1109/ispdc55340.2022.00010","title":"[Full] Deep Heuristic for Broadcasting in Arbitrary Networks","year":2022,"lang":"en","type":"article","venue":"","topic":"Interconnection Networks and Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Heuristics; Computer science; Broadcasting (networking); Heuristic; Vertex (graph theory); Graph; Theoretical computer science; Computer network; Artificial intelligence","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":[0.0007768894,0.0006407876,0.0007357748,0.0007771379,0.0008320247,0.0008237479,0.002040842,0.001234601,0.007798627],"category_scores_gemma":[0.002799832,0.0004395414,0.000632339,0.001021879,0.0007778239,0.001262962,0.001224948,0.001047587,0.001422292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001264809,"about_ca_system_score_gemma":0.002584138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007375482,"about_ca_topic_score_gemma":0.009225304,"domain_scores_codex":[0.9994605,0.0001656106,0.0000249324,0.00007433877,0.0001271273,0.0001475334],"domain_scores_gemma":[0.999005,0.0004100993,0.00006501577,0.000236192,0.0001951455,0.00008855639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003386977,0.0002768757,0.0007316443,0.0002945947,0.000073232,0.0001296611,0.0001666011,0.6580264,0.005846674,0.05898587,0.02219544,0.2529344],"study_design_scores_gemma":[0.00008141616,0.00006479793,0.0001359417,0.00002339666,0.00002671694,0.00004762715,0.00003344261,0.9686648,0.00195972,0.02001433,0.00893222,0.0000156346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03114322,0.0005040079,0.9419063,0.0006859028,0.0002016508,0.0004061505,0.0004820232,0.002338373,0.02233239],"genre_scores_gemma":[0.2570654,0.0002881245,0.7313987,0.0005579866,0.00006114165,0.000395982,0.0009078332,0.0004528885,0.00887189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007798627,"threshold_uncertainty_score":0.02608907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01398063032543269,"score_gpt":0.224557806171605,"score_spread":0.2105771758461723,"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."}}