{"id":"W4246240811","doi":"10.1109/icppw.2004.1328024","title":"A data identi .cation scheme for automatic relative debugging","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Innovation Trust","keywords":"Debugging; Computer science; Scheme (mathematics); Artificial intelligence; Programming language; Mathematics","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":[0.00632133,0.00171666,0.002300381,0.00493982,0.002141832,0.003404689,0.004430479,0.002538614,0.00981406],"category_scores_gemma":[0.01998316,0.001527112,0.001314825,0.003648243,0.001784934,0.008691687,0.005466653,0.003592303,0.004017522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001529795,"about_ca_system_score_gemma":0.002903241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002144675,"about_ca_topic_score_gemma":0.003098757,"domain_scores_codex":[0.9942927,0.001290034,0.0008768093,0.001232022,0.00179586,0.0005126909],"domain_scores_gemma":[0.9789651,0.006528708,0.001296973,0.009388576,0.0032492,0.000571434],"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":[0.001897966,0.0003138864,0.003564063,0.0005320846,0.0001155229,0.0003870996,0.0008360155,0.008740704,0.0480127,0.07743792,0.03150287,0.8266592],"study_design_scores_gemma":[0.0006792006,0.0007496536,0.002098193,0.0003353339,0.0006389809,0.001254344,0.0005007275,0.5048106,0.2432046,0.1683435,0.07686391,0.0005209775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00713842,0.0002885043,0.9697152,0.0002817467,0.000130396,0.0001265285,0.0004211174,0.02120541,0.0006926508],"genre_scores_gemma":[0.145579,0.0001924441,0.8468531,0.0003872362,0.0001317652,0.0002189876,0.001239578,0.001779283,0.003618662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00981406,"threshold_uncertainty_score":0.03343076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06252080480764058,"score_gpt":0.3342574503002166,"score_spread":0.271736645492576,"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."}}