{"id":"W4320015235","doi":"10.2139/ssrn.4328068","title":"Transfer Learning for Conflict and Duplicate Detection in Software Requirement Pairs","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Transfer of learning; Software; Artificial intelligence; Data science; Programming language","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":[0.001999571,0.00008968471,0.00009752972,0.0001738945,0.0001397879,0.00009286393,0.0002141001,0.00005087822,9.751675e-7],"category_scores_gemma":[0.0001276324,0.00008585782,0.00004293454,0.0003030247,0.000009170182,0.000471158,0.00003227362,0.0007735738,0.000002853175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001882241,"about_ca_system_score_gemma":0.0001508143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002311966,"about_ca_topic_score_gemma":0.00006859233,"domain_scores_codex":[0.9986004,0.00004225278,0.0001623505,0.0001828253,0.0001164565,0.0008956947],"domain_scores_gemma":[0.9996034,0.0001898556,0.00003660531,0.00009905593,0.00003093024,0.0000401674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005454956,0.0000243132,0.001640785,0.00003834368,0.00006816453,0.000009232659,0.0007106833,0.004484895,0.003335835,0.0502419,0.00005660214,0.9393347],"study_design_scores_gemma":[0.00505784,0.005804303,0.01266166,0.0002646695,0.0000867178,0.001870404,0.001262165,0.3167673,0.01972145,0.4231282,0.2115716,0.001803578],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08127092,0.0006696352,0.9167786,0.0006508103,0.00008963959,0.0001309925,1.711926e-7,0.0004034427,0.000005823598],"genre_scores_gemma":[0.990778,0.00473302,0.004188185,0.00003849479,0.00005855834,0.0000432079,9.329185e-7,0.00001551473,0.0001440925],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9375311,"threshold_uncertainty_score":0.350118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0207669518550546,"score_gpt":0.2678330052734674,"score_spread":0.2470660534184128,"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."}}