{"id":"W4401851884","doi":"10.53555/sfs.v10i1.2974","title":"Utilizing Machine Learning For Predicting Software Defects","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Software Engineering Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Software; Artificial intelligence; Machine learning; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00205032,0.001140538,0.0007197195,0.005380082,0.000323841,0.0009120221,0.0007806572,0.0011146,0.0005323698],"category_scores_gemma":[0.008374808,0.0002207913,0.0007244304,0.002188022,0.0002185502,0.001172606,0.0004477855,0.0007844125,0.0004873248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005724675,"about_ca_system_score_gemma":0.0007987277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006125263,"about_ca_topic_score_gemma":0.007477395,"domain_scores_codex":[0.9986687,0.0003989469,0.0001307163,0.0002835524,0.0003918011,0.000126339],"domain_scores_gemma":[0.9940715,0.003848355,0.0006521198,0.0003307336,0.0009753776,0.0001218011],"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":[0.0003015585,0.001023045,0.1502287,0.0002712338,0.0002673947,0.0002456259,0.0001146498,0.2755826,0.0048441,0.0008800238,0.005709652,0.5605315],"study_design_scores_gemma":[0.00001178715,0.0001290375,0.00917374,0.00003122356,0.00003523883,0.00006562255,0.00003709942,0.9862903,0.00240725,0.001094849,0.0007072362,0.00001666413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7004005,0.00236709,0.2842522,0.000776756,0.00017652,0.0003185668,0.002839362,0.005157801,0.003711289],"genre_scores_gemma":[0.9226679,0.0004048792,0.07264075,0.00008792352,0.00005920456,0.00010521,0.003154237,0.00003388567,0.0008460325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006125263,"threshold_uncertainty_score":0.01217926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1768960612467354,"score_gpt":0.3131164870256894,"score_spread":0.1362204257789541,"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."}}