{"id":"W4401863136","doi":"10.1145/3637528.3671549","title":"Multi-task Conditional Attention Network for Conversion Prediction in Logistics Advertising","year":2024,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Task (project management); Purchasing; Preference; Online and offline; Business; Marketing; 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":[0.001270482,0.001369101,0.001060355,0.001822406,0.0006131162,0.0008347923,0.001550564,0.0012981,0.002546655],"category_scores_gemma":[0.004342508,0.0005122479,0.001088031,0.001803687,0.0003981913,0.001492167,0.0006741189,0.002360208,0.0009816726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001651789,"about_ca_system_score_gemma":0.00113569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06026103,"about_ca_topic_score_gemma":0.06493545,"domain_scores_codex":[0.9992942,0.0001674892,0.00004047544,0.000255312,0.000115167,0.0001272908],"domain_scores_gemma":[0.997787,0.00140536,0.0001527477,0.0001388039,0.0004226695,0.0000934337],"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":[0.001093182,0.00101447,0.02957147,0.0003192493,0.000428786,0.000579053,0.0003128842,0.4724893,0.006674579,0.005719029,0.02189111,0.4599068],"study_design_scores_gemma":[0.000007067109,0.00001812468,0.001592062,0.000006359855,0.00003002715,0.00002972034,0.000008796912,0.9964774,0.0004178995,0.0009975893,0.0004062119,0.00000866909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2972324,0.005303359,0.6763524,0.002054732,0.0004823967,0.0002686332,0.002374637,0.00495622,0.01097516],"genre_scores_gemma":[0.9258278,0.0008448062,0.0603742,0.0005326757,0.0003176043,0.0001439396,0.0031839,0.0001240178,0.008651029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06026103,"threshold_uncertainty_score":0.1198206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.031104424351742,"score_gpt":0.2837868525268764,"score_spread":0.2526824281751344,"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."}}