{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007744128,0.00002030356,0.00002230041,0.0000132695,0.0002403967,0.0003843116,0.000748977,0.000009905057,0.00007490277],"category_scores_gemma":[0.00001728207,0.00001471529,0.00001368372,0.00001449585,0.00001598957,0.0009061819,0.0001643981,0.00002447467,0.0005309467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003139902,"about_ca_system_score_gemma":0.0000134903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001714452,"about_ca_topic_score_gemma":0.000001566686,"domain_scores_codex":[0.9997438,0.000002426607,0.00004181418,0.00004452241,0.00009368216,0.00007373041],"domain_scores_gemma":[0.9994684,0.000003619778,0.00002008132,0.0004441658,0.00002931113,0.00003438031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000001118051,0.00001185527,0.004132102,0.000002105307,0.00000132199,0.000007185173,0.0001927376,5.905775e-7,0.0002894199,0.7721344,0.002767004,0.2204602],"study_design_scores_gemma":[0.0005010795,0.00009711352,0.7295088,0.000004883124,0.000001106672,0.00001931403,0.00002193683,0.03801006,0.02629483,0.004991625,0.2002949,0.0002544375],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06290205,0.000002051598,0.4935652,0.003691271,0.0003336256,0.00006145295,3.9523e-7,0.0001541446,0.4392898],"genre_scores_gemma":[0.9771448,0.000001528515,0.01494333,0.0002728076,0.00001364048,0.00000150017,1.406639e-7,6.236846e-7,0.007621589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9142428,"threshold_uncertainty_score":0.6824423,"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."}}