{"id":"W2005680430","doi":"10.1109/tse.2014.2383381","title":"Range Fixes: Interactive Error Resolution for Software Configuration","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Software Engineering","topic":"Software Engineering Research","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Range (aeronautics); Constraint (computer-aided design); Software; Simple (philosophy); Theoretical computer science; String (physics); 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":[0.004688331,0.002599322,0.0009901886,0.004095249,0.001101787,0.002341328,0.003618548,0.002163877,0.01240303],"category_scores_gemma":[0.02738161,0.001279212,0.001756793,0.001918856,0.002202046,0.003859596,0.005157712,0.002166643,0.003198738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007963846,"about_ca_system_score_gemma":0.00117315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002241409,"about_ca_topic_score_gemma":0.003552598,"domain_scores_codex":[0.9951283,0.001520052,0.0004017808,0.0009679686,0.001697051,0.0002848058],"domain_scores_gemma":[0.9854344,0.009190155,0.001078622,0.003374191,0.0007235769,0.0001989785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006146823,0.0002270844,0.008296364,0.001087737,0.0002093676,0.0007440522,0.002068431,0.09919992,0.01525053,0.02960861,0.03743199,0.8052613],"study_design_scores_gemma":[0.0002639865,0.0003101983,0.002606599,0.0004974145,0.0001393155,0.001359259,0.0005889663,0.7919218,0.04924295,0.07973276,0.07305857,0.0002782],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01043408,0.0003401022,0.9291871,0.00013778,0.00006704961,0.0001981373,0.0007314586,0.05631746,0.002586868],"genre_scores_gemma":[0.1372999,0.0002073386,0.8520986,0.0001292249,0.00003216625,0.0004073155,0.001858245,0.006250191,0.001717044],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01240303,"threshold_uncertainty_score":0.04149228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01912600793662666,"score_gpt":0.2607286729294038,"score_spread":0.2416026649927771,"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."}}