{"id":"W4378419570","doi":"10.1007/978-3-031-33380-4_2","title":"Online Volume Optimization for Notifications via Long Short-Term Value Modeling","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Volume (thermodynamics); Key (lock); Term (time); Task (project management); Human–computer interaction; World Wide Web; Computer security","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00205591,0.0003462382,0.0004072465,0.001559385,0.0004372983,0.0009324258,0.002116845,0.0002305102,0.0001013283],"category_scores_gemma":[0.0003731448,0.0003018814,0.0001989534,0.0009255368,0.0002587305,0.0009679123,0.0005169906,0.0003418241,0.0001333257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001742393,"about_ca_system_score_gemma":0.000196223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000812933,"about_ca_topic_score_gemma":0.00009518542,"domain_scores_codex":[0.9956847,0.00002114411,0.001032699,0.001042449,0.00178931,0.0004297207],"domain_scores_gemma":[0.9972738,0.0005630078,0.000293503,0.0009275587,0.0008143351,0.0001278078],"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":[0.0000039413,0.00001625894,0.0001495162,0.00000868914,0.000004066787,0.000002693469,0.0002142955,0.8228313,0.000005311703,0.0008121853,0.00004789592,0.1759038],"study_design_scores_gemma":[0.000109787,0.00003781236,0.0004112037,0.00008537435,0.00002123194,0.000003321369,0.000001370954,0.9760613,0.00001009547,0.02272006,0.0001977547,0.0003407035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006551965,0.00003051006,0.9957284,0.0008969792,0.001467527,0.0006944429,0.0000756511,0.0001329707,0.0003182944],"genre_scores_gemma":[0.2587713,0.00006478492,0.7234653,0.001726368,0.001406742,0.00009527603,0.0007753586,0.0001350781,0.01355984],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2722632,"threshold_uncertainty_score":0.9999433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2275045262761207,"score_gpt":0.3991392087833022,"score_spread":0.1716346825071816,"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."}}