{"id":"W3134384212","doi":"10.1145/3406522.3446021","title":"Tip of the Tongue Known-Item Retrieval","year":2021,"lang":"en","type":"article","venue":"","topic":"Expert finding and Q&A systems","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada)","funders":"","keywords":"Information retrieval; Computer science; Tip of the tongue; Identifier; Context (archaeology); Cognitive models of information retrieval; Human–computer information retrieval; Information needs; Cognition; Search engine; World Wide Web; Psychology; Linguistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001808831,0.00005396692,0.00009751898,0.00001789305,0.00006066866,0.00004860223,0.0005591806,0.00003969881,0.00003496385],"category_scores_gemma":[0.00009432945,0.00003270253,0.00007199433,0.0004290589,0.0000207807,0.00007938589,0.0002553564,0.00006278386,0.00003722131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001473701,"about_ca_system_score_gemma":0.00008656914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003814778,"about_ca_topic_score_gemma":0.00001350555,"domain_scores_codex":[0.9992633,0.00007127976,0.0001512915,0.0001754314,0.0002185386,0.0001201863],"domain_scores_gemma":[0.9991241,0.00008967148,0.00004628454,0.000623064,0.00008503847,0.00003180522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008009284,0.0002116691,0.01749478,0.00008918915,0.00007353314,0.00007077315,0.007066532,0.00003978531,0.1314254,0.7539862,0.0764325,0.01310156],"study_design_scores_gemma":[0.0004270091,0.00006143552,0.01123343,0.0001355498,0.000005617088,0.0001713179,0.0003451185,0.01538254,0.8610081,0.001331785,0.1096217,0.0002763712],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4779012,0.00169985,0.1203322,0.01117483,0.007440885,0.000299176,0.000004640162,0.0004144492,0.3807328],"genre_scores_gemma":[0.9740897,0.000003788307,0.002447441,0.0002291342,0.00007981649,8.031233e-7,2.675892e-7,0.000003279852,0.02314577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7526544,"threshold_uncertainty_score":0.133357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01578652067899109,"score_gpt":0.2342781393179661,"score_spread":0.218491618638975,"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."}}