{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008740128,0.001607405,0.001830494,0.001743901,0.003640552,0.002092479,0.003072955,0.002518208,0.01265508],"category_scores_gemma":[0.0350465,0.0007703431,0.0007640295,0.003719833,0.001107671,0.003869751,0.001607647,0.002618716,0.005004578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004432694,"about_ca_system_score_gemma":0.004546446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1828633,"about_ca_topic_score_gemma":0.208652,"domain_scores_codex":[0.9898468,0.00541449,0.0005842426,0.00154901,0.002127661,0.0004779139],"domain_scores_gemma":[0.964074,0.02362895,0.0008945421,0.003914995,0.005325012,0.002162487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.010977,0.01439147,0.01985696,0.003895808,0.0009320612,0.0006633989,0.002856076,0.03945339,0.01937107,0.00246331,0.4817122,0.4034273],"study_design_scores_gemma":[0.009393843,0.008971638,0.09643432,0.000846573,0.001150868,0.000775324,0.006313853,0.6733085,0.04019113,0.006049659,0.15564,0.0009242605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8498437,0.009122601,0.01816944,0.005218954,0.001593718,0.003568158,0.02765585,0.0283323,0.05649526],"genre_scores_gemma":[0.8015736,0.002051233,0.09807819,0.00162536,0.0005813411,0.001709237,0.06631204,0.001576926,0.02649205],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1828633,"threshold_uncertainty_score":0.3635979,"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."}}