{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005510871,0.00008252477,0.0001297847,0.00009040268,0.0002338651,0.0000889978,0.00045654,0.00002535557,0.0000780865],"category_scores_gemma":[0.00002125398,0.00008156183,0.00006425423,0.0003589923,0.000007026511,0.0001393233,0.0002340727,0.0001840607,0.000004022402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006583286,"about_ca_system_score_gemma":0.00002236872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004114341,"about_ca_topic_score_gemma":0.00007037247,"domain_scores_codex":[0.9989466,0.00009302977,0.0002686188,0.0002821039,0.0001262724,0.0002833712],"domain_scores_gemma":[0.9994156,0.0002335574,0.00006105738,0.0002234354,0.0000256709,0.00004063828],"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":[0.00005128883,0.0001008959,0.000749762,0.00002203702,0.00001675389,0.00004768772,0.000988072,0.7620164,0.00002283901,0.2001619,0.01081375,0.02500866],"study_design_scores_gemma":[0.0002339402,0.000144327,0.00009724185,0.000006488559,9.068753e-7,0.00006235094,0.0001620317,0.9898587,0.000003018224,0.001781222,0.007540465,0.0001092655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004109183,0.000183463,0.9872867,0.0002234623,0.001694357,0.0002308251,4.698265e-7,0.0001111781,0.006160362],"genre_scores_gemma":[0.9886394,0.000001393033,0.009380248,0.0008007628,0.0002234569,0.0001738351,0.000002321494,0.00000864266,0.0007699529],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9845302,"threshold_uncertainty_score":0.3325995,"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."}}