{"id":"W2345881254","doi":"10.1145/2851581.2892334","title":"PaperQuest","year":2016,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Focus (optics); sort; Citation; Information retrieval; Visualization; Component (thermodynamics); Key (lock); Reading (process); Data science; World Wide Web; Data mining","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":[0.00003689161,0.00001911821,0.00001909449,0.00001414944,0.0000134607,0.00003387428,0.000235974,0.000006545478,0.0001974588],"category_scores_gemma":[0.00001530556,0.00000959099,0.000007828411,0.00006882998,0.000007016895,0.0002409368,0.00006247289,0.000004267938,0.0007046462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003382638,"about_ca_system_score_gemma":0.000007999437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001126483,"about_ca_topic_score_gemma":0.00000149927,"domain_scores_codex":[0.999783,0.000005520565,0.00003814283,0.00007082146,0.00005254726,0.00004993919],"domain_scores_gemma":[0.9997596,0.00001365889,0.000007206757,0.0001771948,0.00001513105,0.00002725527],"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":[3.6324e-8,0.000004781516,0.0002672232,2.13925e-7,6.522584e-7,6.382345e-7,0.00000542211,4.037764e-8,0.0005690082,0.9456,0.01301118,0.04054077],"study_design_scores_gemma":[0.000210523,0.00002068803,0.001483269,0.000008641673,7.989693e-7,0.000003796975,0.000003327619,0.006961421,0.006648089,0.01042059,0.9741204,0.0001184636],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00007411977,0.000002297068,0.9538034,0.002752643,0.00005107652,0.000006754565,4.602688e-7,0.0001098174,0.04319945],"genre_scores_gemma":[0.8852257,0.00004559106,0.04480658,0.00598984,0.00006490885,0.000001441676,0.000001305991,0.000004250783,0.06386044],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9611092,"threshold_uncertainty_score":0.9057036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01875055119751902,"score_gpt":0.2830697176278619,"score_spread":0.2643191664303429,"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."}}