{"id":"W2740321901","doi":"10.1145/3077136.3080721","title":"Anserini","year":2017,"lang":"en","type":"article","venue":"","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":323,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Scalability; Ranking (information retrieval); Information retrieval; Search engine indexing; World Wide Web; Database","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003035212,0.001722615,0.001246716,0.003326435,0.00167828,0.004832644,0.002804007,0.001628622,0.1996145],"category_scores_gemma":[0.0114126,0.001188533,0.001467907,0.002446195,0.0008671345,0.007220777,0.005014215,0.002170104,0.2277051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001730875,"about_ca_system_score_gemma":0.002536446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004226551,"about_ca_topic_score_gemma":0.00464728,"domain_scores_codex":[0.9966182,0.0005523411,0.0002887806,0.0007440951,0.00149932,0.0002972],"domain_scores_gemma":[0.995297,0.001035278,0.0002410587,0.001576631,0.001414044,0.0004359721],"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":[0.0004993593,0.0001490497,0.001358859,0.0007519377,0.00005608398,0.0002156348,0.000498173,0.001321568,0.009000601,0.03484727,0.5037453,0.4475561],"study_design_scores_gemma":[0.00005087497,0.00007966298,0.0009742782,0.0001201195,0.00002431092,0.0003400307,0.00006038194,0.007184939,0.007628292,0.01452192,0.9689315,0.00008356144],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"software","genre_scores_codex":[0.006902224,0.003170676,0.2734137,0.002720429,0.001332189,0.001017522,0.02176412,0.3391314,0.3505478],"genre_scores_gemma":[0.05103498,0.002620186,0.3165924,0.002587281,0.0007393798,0.001527313,0.0809017,0.04991461,0.4940822],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1996145,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03590055928300059,"score_gpt":0.3085574560823229,"score_spread":0.2726568967993224,"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."}}