{"id":"W4392669853","doi":"10.18653/v1/2023.ijcnlp-main.46","title":"Analyzing and Predicting Persistence of News Tweets","year":2023,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Persistence (discontinuity); Computational linguistics; Computer science; Joint (building); Volume (thermodynamics); Association (psychology); Natural language processing; Artificial intelligence; Linguistics; Data science; Library science; Engineering; Philosophy; Epistemology","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":[0.0009955748,0.0004586238,0.0004619699,0.003971891,0.0005085582,0.001307874,0.0003836435,0.0005343146,0.0008370708],"category_scores_gemma":[0.006534713,0.0002785685,0.0004019143,0.002441293,0.0001986583,0.001534114,0.0006335588,0.0007935442,0.001203169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003216842,"about_ca_system_score_gemma":0.0002803975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004078113,"about_ca_topic_score_gemma":0.006790382,"domain_scores_codex":[0.9995961,0.00008416229,0.00003197125,0.000119398,0.000092452,0.00007602632],"domain_scores_gemma":[0.995937,0.002372561,0.0005428529,0.0002737472,0.0005942208,0.0002797145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001751048,0.0005220819,0.6543933,0.0006714941,0.0006025894,0.0006609852,0.001152,0.009761646,0.01538663,0.002601677,0.05060002,0.2618965],"study_design_scores_gemma":[0.0001004386,0.000524319,0.5023532,0.000200766,0.0007329815,0.0007560747,0.003572123,0.4408259,0.01371883,0.006519729,0.03057699,0.0001185219],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9694559,0.004174219,0.01107092,0.001320704,0.0004570595,0.0000685882,0.009836595,0.0006157595,0.003000154],"genre_scores_gemma":[0.9792838,0.001107134,0.004421202,0.00007147475,0.0005755372,0.00005039959,0.01263594,0.00007147735,0.001782917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004078113,"threshold_uncertainty_score":0.008108795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05018962379470674,"score_gpt":0.2570065668108198,"score_spread":0.2068169430161131,"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."}}