{"id":"W2964507227","doi":"","title":"Entity Retrieval Docker Image for OSIRRC at SIGIR 2019.","year":2019,"lang":"en","type":"article","venue":"International ACM SIGIR Conference on Research and Development in Information Retrieval","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Information retrieval; Natural language processing; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004241883,0.002032607,0.002092869,0.004834651,0.002164147,0.009368203,0.003359588,0.00374546,0.8238291],"category_scores_gemma":[0.008000875,0.0009293553,0.001402836,0.003395805,0.0006868541,0.007930278,0.004389193,0.00274833,0.769774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001557478,"about_ca_system_score_gemma":0.0027394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008958125,"about_ca_topic_score_gemma":0.01378063,"domain_scores_codex":[0.9983523,0.0001348568,0.00005978997,0.0002968818,0.0009297775,0.0002264735],"domain_scores_gemma":[0.9927649,0.0007920847,0.0002362582,0.001061345,0.00230057,0.002844901],"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":[0.00003961383,0.00001890031,0.00001864726,0.00002959131,0.000002029562,0.00001067259,0.000005234961,0.00002194916,0.0002283563,0.0003707478,0.9883519,0.01090244],"study_design_scores_gemma":[0.00004541233,0.00003973628,0.0001955187,0.00004059667,0.000005126008,0.00003605728,0.00001896865,0.0004706813,0.0003872249,0.00114912,0.9975954,0.00001613335],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"software","genre_scores_codex":[0.00168512,0.003907439,0.02873918,0.02385739,0.02883297,0.0009272718,0.08982072,0.1329444,0.6892856],"genre_scores_gemma":[0.002787028,0.0008545135,0.009940381,0.001946617,0.003264525,0.0001592431,0.05595017,0.009907455,0.91519],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.8238291,"threshold_uncertainty_score":0.2512864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2349553371768173,"score_gpt":0.4577698368885389,"score_spread":0.2228144997117216,"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."}}