{"id":"W3153794000","doi":"10.48550/arxiv.2104.05740","title":"A Replication Study of Dense Passage Retriever","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Topic Modeling","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Replication (statistics); Labrador Retriever; Business; Biology; Medicine; Virology; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01487682,0.001100609,0.001787766,0.001268081,0.0009351211,0.001580651,0.00308038,0.001836252,0.005806371],"category_scores_gemma":[0.06031675,0.0005093985,0.001485489,0.00116091,0.00141041,0.006236387,0.002232576,0.00292445,0.004674888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001141998,"about_ca_system_score_gemma":0.001277837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007010292,"about_ca_topic_score_gemma":0.003617218,"domain_scores_codex":[0.9885055,0.006893657,0.0005765496,0.00207136,0.001666627,0.0002863419],"domain_scores_gemma":[0.9477195,0.02295699,0.001091228,0.02181836,0.005737009,0.0006769903],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006388954,0.006074863,0.01497838,0.003120526,0.001255212,0.0007939509,0.002649225,0.07912234,0.05204859,0.02754389,0.07715376,0.7288703],"study_design_scores_gemma":[0.002721443,0.009047044,0.01657107,0.0002239592,0.0007990546,0.001339167,0.001218894,0.7967954,0.06076034,0.04662157,0.06342117,0.0004809463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6238068,0.006853176,0.3095414,0.004677685,0.001349599,0.003009409,0.007139128,0.0180208,0.02560196],"genre_scores_gemma":[0.8127333,0.0006589335,0.1643973,0.001567894,0.0006272835,0.001155724,0.008662431,0.0008078008,0.009389372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9851232,"threshold_uncertainty_score":0.07867712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1032666392796188,"score_gpt":0.2051160122093425,"score_spread":0.1018493729297237,"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."}}