{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002586389,0.00002298089,0.00002244074,0.00003957656,0.00002902017,0.00004706828,0.0004677255,0.000007191581,0.00002570527],"category_scores_gemma":[0.0003243051,0.00001918002,0.00000554481,0.000262175,0.000009030271,0.0001062016,0.0001395302,0.00002550582,0.0004298687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001187819,"about_ca_system_score_gemma":0.00001173526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000173039,"about_ca_topic_score_gemma":0.000003130403,"domain_scores_codex":[0.9995351,0.0000100456,0.0000410025,0.0002003235,0.0001315568,0.00008193039],"domain_scores_gemma":[0.9988335,0.00007489471,0.000004788599,0.0009979677,0.00006185661,0.00002699054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005493249,0.000684239,0.4756529,0.000006952745,0.00003775158,0.00001737022,0.005934746,0.00001447774,0.003276476,0.07264302,0.03805721,0.4036694],"study_design_scores_gemma":[0.0002677451,0.0007082316,0.9459409,0.000002283987,8.628402e-7,0.000007819235,0.00004020268,0.0335411,0.008268022,0.0009614092,0.01012454,0.0001368614],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2778772,0.000002307278,0.7192491,0.0002125103,0.00007780304,0.0001010605,1.868273e-8,0.0004211155,0.002058906],"genre_scores_gemma":[0.975999,8.735255e-8,0.02302063,0.000038234,0.00004774572,0.00001279113,4.846787e-8,0.000001950556,0.0008795301],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6981218,"threshold_uncertainty_score":0.5525236,"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."}}