{"id":"W2407299292","doi":"10.1145/2901739.2903499","title":"Analysis of exception handling patterns in Java projects","year":2016,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Java; Computer science; Exception handling; Programming language; Class (philosophy); Class hierarchy; Software bug; Generics in Java; Hierarchy; Software; Scala; Empirical research; Real time Java; Software engineering; Java annotation; Object-oriented programming; Artificial intelligence; Mathematics; Statistics","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":[0.0002620723,0.00004017922,0.00009786706,0.0005706635,0.000006546101,0.00001622984,0.0002903218,0.00002191757,0.00004507023],"category_scores_gemma":[0.0001926687,0.00002608017,0.00003679693,0.001049877,0.000007681387,0.0001759652,0.00009681493,0.00002825652,0.0000107291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003731923,"about_ca_system_score_gemma":0.00001999195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001371843,"about_ca_topic_score_gemma":0.00009656807,"domain_scores_codex":[0.9993714,0.0000201712,0.0001151464,0.0001642927,0.0001919725,0.0001370091],"domain_scores_gemma":[0.9993368,0.0002977348,0.00001827802,0.0002828167,0.00003923611,0.00002512468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[9.314337e-7,0.00001705766,0.9522086,0.000007289057,0.00003325065,0.000002668113,0.0002397974,0.000353459,0.00378877,0.0003159627,0.0000109166,0.04302131],"study_design_scores_gemma":[0.0001438818,0.00002160988,0.9619653,0.00002908909,0.000005913131,3.022659e-7,0.000005399737,0.03094749,0.006772664,0.00004170294,0.00001084776,0.00005578583],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4802889,0.000003646301,0.5195358,0.00005505564,0.00001971791,0.00002733669,3.631726e-7,0.00003806394,0.0000311748],"genre_scores_gemma":[0.9963759,0.00000599422,0.00343516,0.000006333179,0.000007694599,0.00000626466,3.242688e-7,0.000002340174,0.0001600385],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5161006,"threshold_uncertainty_score":0.1063518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02690261555388055,"score_gpt":0.2799268856200367,"score_spread":0.2530242700661561,"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."}}