{"id":"W3008204235","doi":"10.5539/mas.v14n3p30","title":"Parallel Whale Optimization Algorithm for Maximum Flow Problem","year":2020,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Maximum flow problem; Computer science; Algorithm; Speedup; Optimization algorithm; Whale; Flow (mathematics); Graph; Parallel computing; Mathematical optimization; Theoretical computer science; Mathematics","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":[0.0006754697,0.0008977494,0.001089592,0.0009288751,0.0008716468,0.0008536808,0.001257923,0.0009370495,0.006336369],"category_scores_gemma":[0.001488111,0.000385664,0.0009353546,0.001274007,0.0004563644,0.001124035,0.0009647134,0.0009508477,0.000827555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006051669,"about_ca_system_score_gemma":0.001603589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005807948,"about_ca_topic_score_gemma":0.006187165,"domain_scores_codex":[0.9994955,0.0001113946,0.00002624235,0.0001259121,0.00015794,0.00008294029],"domain_scores_gemma":[0.9996819,0.0001479411,0.00003424997,0.00003451949,0.00008053041,0.00002082204],"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":[0.0001483802,0.0001283401,0.000745917,0.0002160857,0.00009354133,0.0001526264,0.00008940446,0.7806829,0.002791466,0.02765024,0.00838037,0.1789207],"study_design_scores_gemma":[0.0000444041,0.00004385369,0.0001305082,0.000008718906,0.00001318657,0.0000449091,0.00002220391,0.9836735,0.0009009892,0.01076919,0.004340243,0.000008295482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01313185,0.0003963046,0.9770438,0.0002975426,0.0001373845,0.0001385653,0.0001152454,0.0006615268,0.008077759],"genre_scores_gemma":[0.2692725,0.0005188772,0.715767,0.0002625952,0.0001327589,0.0006543256,0.0006130379,0.0003337008,0.01244522],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006336369,"threshold_uncertainty_score":0.02119726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03306968845705108,"score_gpt":0.2683707063733685,"score_spread":0.2353010179163174,"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."}}