{"id":"W4239926161","doi":"10.32920/ryerson.14654136.v1","title":"Generating Artificial Data for Scalability Test of a Followee Twitter Recommender System","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Scalability; Recommender system; Computer science; Software deployment; Cloud computing; Test (biology); Machine learning; Task (project management); Artificial intelligence; Software; Data mining; Database; Software engineering; Engineering","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":[0.001921657,0.0004949339,0.0004571708,0.0006118221,0.0004879301,0.0006546885,0.0009037179,0.0009475946,0.001020563],"category_scores_gemma":[0.008952674,0.000248068,0.0005940316,0.00066889,0.00044147,0.0009093015,0.0006387475,0.000922624,0.0004098798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008612112,"about_ca_system_score_gemma":0.0005340854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005314839,"about_ca_topic_score_gemma":0.003492821,"domain_scores_codex":[0.9984677,0.0005571555,0.0001376771,0.000261148,0.0004512017,0.0001249674],"domain_scores_gemma":[0.9921523,0.004432024,0.0003801919,0.001404902,0.001423454,0.0002071342],"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":[0.002134206,0.002832722,0.08176405,0.001029987,0.0005457485,0.0007468285,0.001213556,0.6732299,0.1116758,0.01008826,0.007202322,0.1075366],"study_design_scores_gemma":[0.00006882205,0.0007417763,0.0119887,0.00001941065,0.0000487368,0.0001010681,0.0002226781,0.9511676,0.03192894,0.001845377,0.001827761,0.00003908814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9398184,0.000135683,0.05495016,0.0002284884,0.00009628581,0.0004553933,0.001487009,0.0009740663,0.001854545],"genre_scores_gemma":[0.9512498,0.0000859917,0.04514396,0.00006464935,0.00001957903,0.0003844098,0.001969485,0.00005175975,0.001030317],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005314839,"threshold_uncertainty_score":0.01056778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09490493922037319,"score_gpt":0.3020290099950328,"score_spread":0.2071240707746596,"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."}}