{"id":"W2258726425","doi":"10.1145/2901739.2901766","title":"The unreasonable effectiveness of traditional information retrieval in crash report deduplication","year":2016,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Mozilla Foundation; Mitacs","keywords":"Crash; Computer science; Data deduplication; Software; Scalability; Information retrieval; Precision and recall; Database; Data science; Software engineering; World Wide Web; Operating system","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":[0.01194571,0.001388917,0.001920192,0.005897562,0.001847313,0.004377502,0.003188596,0.002083038,0.00170564],"category_scores_gemma":[0.05289781,0.000698969,0.000933059,0.006978452,0.001710331,0.01057866,0.002104968,0.00169674,0.003480266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00139765,"about_ca_system_score_gemma":0.002261902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004847452,"about_ca_topic_score_gemma":0.006315708,"domain_scores_codex":[0.9899833,0.002731254,0.001238325,0.001710646,0.00384984,0.000486535],"domain_scores_gemma":[0.9415188,0.033097,0.002784892,0.01617038,0.005931886,0.0004970342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001385154,0.0005759579,0.0145197,0.002554147,0.0004354305,0.0004414144,0.001038434,0.02443995,0.04068989,0.004644264,0.04635024,0.8629255],"study_design_scores_gemma":[0.0007602319,0.003863233,0.04527757,0.001022478,0.001189511,0.008083501,0.005336393,0.3945798,0.3711771,0.03737615,0.1305365,0.0007975888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5347606,0.03839009,0.3597619,0.006344651,0.001889402,0.001490439,0.005781776,0.03215655,0.01942459],"genre_scores_gemma":[0.680832,0.006368766,0.2977183,0.001216283,0.0005644481,0.0002869801,0.005545086,0.000920068,0.006548118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01194571,"threshold_uncertainty_score":0.06317568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526597073158071,"score_gpt":0.2492900997646688,"score_spread":0.2340241290330881,"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."}}