{"id":"W2232682432","doi":"10.1177/0165551515614473","title":"Editorial","year":2016,"lang":"es","type":"editorial","venue":"Journal of Information Science","topic":"Expert finding and Q&A systems","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of British Columbia","keywords":"Computer science; Variety (cybernetics); Set (abstract data type); Cognitive models of information retrieval; Information retrieval; Information needs; Online search; Information seeking; Field (mathematics); World Wide Web; Perspective (graphical); Data science; Search engine; Human–computer information retrieval; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002523622,0.001357467,0.001227473,0.002155235,0.002148939,0.006378102,0.00253524,0.005127605,0.2481316],"category_scores_gemma":[0.0163835,0.0004829001,0.001216931,0.001022089,0.001319412,0.004169783,0.002020549,0.005981345,0.1457516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001923052,"about_ca_system_score_gemma":0.002860046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009182002,"about_ca_topic_score_gemma":0.001435849,"domain_scores_codex":[0.9967095,0.0003837266,0.0002799107,0.0007802297,0.001464105,0.0003825406],"domain_scores_gemma":[0.9880049,0.002074063,0.0007184317,0.001006787,0.005590064,0.002605779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002289328,0.00001020722,0.00005216436,0.0001179915,0.00000378023,0.0001094681,0.00001706662,0.00001611,0.00007764991,0.0009213855,0.9849488,0.01370248],"study_design_scores_gemma":[0.000008642834,0.000009454136,0.0001205841,0.0001350221,0.000003786679,0.0001952017,0.000032362,0.00002275113,0.00007554092,0.0005727176,0.9988193,0.000004504596],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0002477322,0.006550375,0.0004532707,0.04771027,0.8878432,0.00007096935,0.0007052334,0.0003779904,0.05604089],"genre_scores_gemma":[0.004513204,0.009726038,0.0006440795,0.05066387,0.7100471,0.0001106168,0.001291446,0.0004151638,0.2225885],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.2481316,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008593887028867568,"score_gpt":0.2862305538817965,"score_spread":0.277636666852929,"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."}}