{"id":"W3191854875","doi":"10.32920/ryerson.14657001.v1","title":"Retweet Prediction Based on User Behavior","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Baseline (sea); Matrix decomposition; Regularization (linguistics); Focus (optics); Field (mathematics); Social network (sociolinguistics); Artificial intelligence; Machine learning; Factorization; Non-negative matrix factorization; User information; Information retrieval; Social media; World Wide Web; Information system; Mathematics","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":[0.000910315,0.001335199,0.0007913674,0.002294448,0.0004106291,0.0007088411,0.0006787676,0.0008911064,0.001027838],"category_scores_gemma":[0.005449784,0.0003070479,0.0008542593,0.001297925,0.0002487485,0.001891308,0.0003878575,0.001150872,0.00134759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004668759,"about_ca_system_score_gemma":0.0003395634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01085243,"about_ca_topic_score_gemma":0.01443778,"domain_scores_codex":[0.9993032,0.0001199146,0.00005672632,0.0002277912,0.0001915304,0.0001008503],"domain_scores_gemma":[0.9960862,0.00184311,0.0006320043,0.0003924457,0.0008731658,0.0001730864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00128262,0.001114465,0.2920748,0.0003861186,0.0004465815,0.001146667,0.0006799236,0.2153313,0.04059664,0.002841327,0.008787092,0.4353124],"study_design_scores_gemma":[0.000004635555,0.00009900417,0.02234796,0.00001191081,0.00004647039,0.0001382636,0.00004199852,0.9712142,0.004531186,0.0008512023,0.0006894289,0.00002375973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7735639,0.001218024,0.2158166,0.00046573,0.0001801523,0.0002201644,0.002380422,0.002398322,0.003756631],"genre_scores_gemma":[0.9684432,0.0003524865,0.02545049,0.00003995479,0.00006996719,0.00005984046,0.001929753,0.00005697343,0.003597415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01085243,"threshold_uncertainty_score":0.02157849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01801611141014242,"score_gpt":0.2768807386734231,"score_spread":0.2588646272632806,"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."}}