{"id":"W4327909872","doi":"10.1145/3576840.3578288","title":"Taking Search to Task","year":2023,"lang":"en","type":"article","venue":"","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada)","funders":"National Science Foundation","keywords":"Computer science; Task (project management); Data science; Human–computer interaction; World Wide Web","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":[0.008284583,0.001876846,0.001641128,0.004370448,0.005013799,0.01556959,0.002403707,0.005945393,0.01510176],"category_scores_gemma":[0.03510848,0.0009716437,0.001482986,0.003821743,0.01788917,0.03538329,0.0116027,0.009047275,0.00396015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005043404,"about_ca_system_score_gemma":0.004472112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01018785,"about_ca_topic_score_gemma":0.006969213,"domain_scores_codex":[0.9917354,0.004103889,0.0004287993,0.001781638,0.001360467,0.000589693],"domain_scores_gemma":[0.9856992,0.008366126,0.0007625174,0.002270856,0.001966484,0.0009348449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008906815,0.00002356623,0.0007406475,0.0003201048,0.0000356613,0.0001241862,0.004693727,0.001447922,0.0004152814,0.932606,0.01423055,0.04527339],"study_design_scores_gemma":[0.00002263962,0.00003333262,0.0003538717,0.0001812997,0.00003179641,0.0001509618,0.002459804,0.0033897,0.0002951607,0.916909,0.07613102,0.00004143424],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0191022,0.02398995,0.5573727,0.1416361,0.004157872,0.0003209618,0.001157443,0.0008787643,0.2513841],"genre_scores_gemma":[0.6940938,0.01386004,0.212454,0.0204954,0.003347079,0.0009233538,0.00161027,0.001016732,0.05219938],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01556959,"threshold_uncertainty_score":0.05052042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03618877596297738,"score_gpt":0.2906310978222022,"score_spread":0.2544423218592248,"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."}}