{"id":"W2887758210","doi":"10.1145/3194104.3194110","title":"A replication study","year":2018,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Preprocessor; Ensemble learning; Random forest; Replication (statistics); Replicate; Artificial intelligence; Machine learning; Software bug; Debugging; Layer (electronics); Process (computing); Code (set theory); Set (abstract data type); Deep learning; Data mining; Software; Source code; Programming language; Statistics; Mathematics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05584734,0.001650825,0.001743892,0.001360241,0.002508232,0.003183426,0.002721115,0.00282681,0.01274251],"category_scores_gemma":[0.1711249,0.0008880651,0.003782616,0.001697937,0.001984354,0.004215358,0.003053101,0.004710257,0.006277941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002212168,"about_ca_system_score_gemma":0.005286314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006041171,"about_ca_topic_score_gemma":0.005159718,"domain_scores_codex":[0.9531411,0.02187322,0.004529313,0.009779351,0.009436185,0.001240815],"domain_scores_gemma":[0.7946602,0.05955658,0.00877683,0.08693901,0.04700721,0.003060204],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.04520371,0.02329163,0.134344,0.008437704,0.006051427,0.004600727,0.01921513,0.01045563,0.0513814,0.03530445,0.1728904,0.4888238],"study_design_scores_gemma":[0.0173142,0.04865673,0.1854196,0.002622102,0.004862264,0.003205802,0.008637465,0.02165463,0.04470224,0.0540702,0.6076962,0.001158619],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6332984,0.003715208,0.1846751,0.01125375,0.01498662,0.06951496,0.02872212,0.005298425,0.04853546],"genre_scores_gemma":[0.7430692,0.000589839,0.1137713,0.009599769,0.001543608,0.09579622,0.01337889,0.001363458,0.02088767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9441527,"threshold_uncertainty_score":0.2953525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0325642171348209,"score_gpt":0.3293432103664992,"score_spread":0.2967789932316783,"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."}}