{"id":"W2087472619","doi":"10.1109/iwsm-mensura.2011.21","title":"Bidirectional Influence of Defects and Functional Size","year":2011,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Functional requirement; Computer science; Measure (data warehouse); Value (mathematics); Data mining; Machine learning; Software engineering","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":[0.003788777,0.0007928533,0.0006661278,0.00225891,0.0002833928,0.001450388,0.0006866598,0.0006871973,0.004378282],"category_scores_gemma":[0.06163575,0.0005273148,0.0006538421,0.0008668581,0.001133098,0.001331045,0.001459469,0.0012744,0.0006445742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000659094,"about_ca_system_score_gemma":0.0005947098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002288773,"about_ca_topic_score_gemma":0.002192054,"domain_scores_codex":[0.9923227,0.003602694,0.0002433737,0.001074218,0.002390884,0.0003661794],"domain_scores_gemma":[0.7415397,0.2306729,0.01162543,0.007158535,0.006667656,0.002335901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005385895,0.000865316,0.7113686,0.0005576052,0.0007535028,0.001446817,0.001744299,0.01884413,0.111354,0.002512702,0.0006432442,0.144524],"study_design_scores_gemma":[0.00009139716,0.002308379,0.9291956,0.0001125828,0.0009557387,0.00170931,0.0008883339,0.02807617,0.03062238,0.003284517,0.002626431,0.0001290624],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826869,0.001050822,0.008644522,0.0001994998,0.00001969005,0.00003807974,0.0002459412,0.0002030539,0.006911316],"genre_scores_gemma":[0.9978253,0.0001999316,0.001128462,0.00002773218,0.000009138773,0.000009107069,0.0001020045,0.00008710857,0.0006112466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004378282,"threshold_uncertainty_score":0.02003723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02384145946745158,"score_gpt":0.2271931709935922,"score_spread":0.2033517115261406,"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."}}