{"id":"W4408069070","doi":"10.1007/s42484-025-00236-w","title":"Comparative analysis of quantum and classical support vector classifiers for software bug prediction: an exploratory study","year":2025,"lang":"en","type":"article","venue":"Quantum Machine Intelligence","topic":"Software Engineering Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island; University of Saskatchewan","funders":"","keywords":"Support vector machine; Computer science; Quantum; Software; Exploratory research; Artificial intelligence; Machine learning; Physics; Programming language; Quantum mechanics; Sociology","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":[],"consensus_categories":[],"category_scores_codex":[0.00735024,0.0003859457,0.0007678556,0.001959914,0.0004603824,0.001268567,0.0008973005,0.0007087468,0.001408462],"category_scores_gemma":[0.03367808,0.0001325875,0.000498702,0.001635927,0.0005313952,0.003048133,0.0005464366,0.0005167796,0.0002742718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007749751,"about_ca_system_score_gemma":0.0007380845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00234896,"about_ca_topic_score_gemma":0.001741655,"domain_scores_codex":[0.9968925,0.001269922,0.0001835075,0.0003876119,0.001098835,0.0001677631],"domain_scores_gemma":[0.9498112,0.042509,0.001327776,0.001344267,0.004670994,0.0003366666],"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":[0.004879621,0.001958658,0.1624197,0.001023592,0.001008613,0.0002397414,0.0007186189,0.09750018,0.007404196,0.01535956,0.004903529,0.7025841],"study_design_scores_gemma":[0.0001120195,0.001796578,0.04744561,0.0000720071,0.0003591243,0.0002174212,0.0007276663,0.9355704,0.002951408,0.009076138,0.001627617,0.00004400857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9590218,0.002393642,0.03462652,0.0003866654,0.00005500311,0.00005582024,0.0002456287,0.0002154835,0.00299938],"genre_scores_gemma":[0.9917029,0.0002851639,0.007355781,0.00003104599,0.00002961766,0.00001610603,0.0002345687,0.00001573288,0.000329113],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00735024,"threshold_uncertainty_score":0.03887224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05253343009886388,"score_gpt":0.3542913731986322,"score_spread":0.3017579430997683,"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."}}