{"id":"W4403155837","doi":"10.1007/s10115-024-02248-7","title":"Deep-transfer learning inspired natural language processing system for software requirements classification","year":2024,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Software Engineering Research","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Artificial intelligence; Transfer of learning; Natural language processing; Natural language; Deep learning; Software; Machine learning; 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":[0.0005678132,0.000120403,0.0001302432,0.0002950346,0.0001868361,0.001003428,0.0002370012,0.00007431435,4.580106e-7],"category_scores_gemma":[0.0001760567,0.0001051185,0.00003653852,0.0004309257,0.00001428766,0.003911941,0.00005094632,0.0001526829,0.0000799563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001609733,"about_ca_system_score_gemma":0.00008762193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005416822,"about_ca_topic_score_gemma":7.875349e-7,"domain_scores_codex":[0.9989859,0.0000377875,0.0003489505,0.0001764781,0.0002308023,0.0002200131],"domain_scores_gemma":[0.9992977,0.0001959907,0.00003450254,0.0001614622,0.0002454995,0.00006483099],"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":[0.00001415065,0.00001607991,0.001122782,0.01685291,0.0000636144,0.000003594487,0.04052642,0.001032206,0.001006184,0.02369963,0.0006896933,0.9149727],"study_design_scores_gemma":[0.0002274953,0.00003491583,0.0008286851,0.0006516851,0.000005598744,0.00002319902,0.001054274,0.9650781,0.0001861985,0.000001568367,0.03176512,0.0001431711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008455609,0.01083594,0.9771433,0.00002459684,0.001216715,0.0005214913,0.000002846049,0.001203574,0.0005958852],"genre_scores_gemma":[0.998108,0.00001213323,0.001242213,0.000006082027,0.0001290538,0.0001905321,0.00004269623,0.00001138222,0.0002579631],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9896523,"threshold_uncertainty_score":0.967608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0214657515274903,"score_gpt":0.2849039942470497,"score_spread":0.2634382427195593,"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."}}