{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007552629,0.0007257434,0.001475785,0.001913673,0.0009230733,0.001052464,0.0033174,0.002044736,0.002565626],"category_scores_gemma":[0.03642222,0.0005001532,0.000866281,0.001396912,0.0009093219,0.003910579,0.003446961,0.00283989,0.0006756088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293725,"about_ca_system_score_gemma":0.001946235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005065458,"about_ca_topic_score_gemma":0.003403094,"domain_scores_codex":[0.9960705,0.001961987,0.0002708021,0.0006444292,0.0007411494,0.0003110751],"domain_scores_gemma":[0.9486154,0.04352397,0.001492436,0.00290775,0.002809211,0.0006511277],"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":[0.001116597,0.001060862,0.01000673,0.0002486926,0.000229009,0.0002635492,0.0005211646,0.3123203,0.003711761,0.008139657,0.003865778,0.6585158],"study_design_scores_gemma":[0.00001803541,0.00007500476,0.0005097681,0.000006275773,0.00001344895,0.00002491682,0.00005499552,0.9899375,0.001014616,0.008189931,0.0001474845,0.000008010164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1630207,0.000335054,0.8321699,0.0003881938,0.00006466941,0.0002116858,0.0001385922,0.001814958,0.001856262],"genre_scores_gemma":[0.8831298,0.00007369878,0.1139616,0.0001299511,0.00005120226,0.0002006277,0.0003746186,0.00009258818,0.001985901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007552629,"threshold_uncertainty_score":0.03994256,"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."}}