{"id":"W923756419","doi":"","title":"University of Waterloo at TREC 2014 Contextual Suggestion: Experiments with suggestion clustering","year":2014,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Point of interest; Task (project management); Point (geometry); Similarity (geometry); Cluster analysis; Information retrieval; World Wide Web; Special Interest Group; Artificial intelligence; Mathematics","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":[0.0003266698,0.0002224854,0.0003582346,0.0001371799,0.0001730044,0.00005506869,0.0008748384,0.0001065349,0.0001582588],"category_scores_gemma":[0.0000534688,0.0002046282,0.00007064814,0.0003437908,0.0002319749,0.000432529,0.0004367143,0.0001532866,0.0000785789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000147711,"about_ca_system_score_gemma":0.00006714877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002060478,"about_ca_topic_score_gemma":0.00022738,"domain_scores_codex":[0.9983216,0.000156059,0.0002459931,0.0005483609,0.0004311122,0.0002969024],"domain_scores_gemma":[0.9984159,0.0001187243,0.0002632038,0.000735561,0.0003354719,0.0001311282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004294624,0.0009669009,0.03260219,0.0003566082,0.0005350962,0.0001920436,0.02099101,0.002387058,0.4733237,0.124949,0.004742731,0.334659],"study_design_scores_gemma":[0.005035777,0.003535805,0.0253074,0.0006443459,0.0001707885,0.0001262963,0.0007715307,0.3270116,0.6203047,0.002460223,0.01250166,0.002129902],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2630398,0.00003811768,0.7346123,0.0001665248,0.00004889255,0.0001563924,0.000002561728,0.0002773454,0.001658067],"genre_scores_gemma":[0.9694799,0.00002705749,0.02801584,0.00003211186,0.00001971423,0.000001014999,0.000009070095,0.00001115856,0.002404146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7065965,"threshold_uncertainty_score":0.8344494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01781061543086193,"score_gpt":0.2403849172981885,"score_spread":0.2225743018673266,"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."}}