{"id":"W3153341352","doi":"","title":"A Mixed Method Approach to investigate the Antecedents of Software Quality and Information Systems Success in Canadian Software Development Firms","year":2018,"lang":"en","type":"article","venue":"Electronic Journal of Information Systems Evaluation","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Software development; Software quality control; Software quality analyst; Software quality; Software quality management; Knowledge management; Personal software process; Quality (philosophy); Software development process; Computer science; Team software process; Capability Maturity Model; Process management; Software; Software construction; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01426821,0.001366553,0.002045904,0.008629496,0.01221607,0.003167145,0.003654716,0.001494578,0.005966012],"category_scores_gemma":[0.01934681,0.001175109,0.001669862,0.01295602,0.002184338,0.001184971,0.002710831,0.002112444,0.0004503074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05316407,"about_ca_system_score_gemma":0.08238816,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8853216,"about_ca_topic_score_gemma":0.9220272,"domain_scores_codex":[0.9864897,0.006330474,0.000724112,0.001267748,0.002664525,0.002523515],"domain_scores_gemma":[0.9796321,0.008880288,0.002041282,0.001014863,0.007325338,0.001106054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.002985113,0.01511088,0.4897566,0.004551902,0.001132741,0.001883638,0.1434063,0.005886384,0.006254793,0.02980113,0.009577278,0.2896532],"study_design_scores_gemma":[0.002140005,0.01093282,0.6170534,0.001857996,0.001724096,0.0003224949,0.2917659,0.02347018,0.005359157,0.007062791,0.03784862,0.000462471],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9372886,0.001280035,0.01492881,0.0008013888,0.0001340621,0.02972749,0.003007169,0.00007473741,0.01275774],"genre_scores_gemma":[0.8131934,0.001851379,0.08686226,0.001282694,0.0000758017,0.08000194,0.001852256,0.00004157149,0.01483862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1146784,"threshold_uncertainty_score":0.3857341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04477827666326525,"score_gpt":0.3242448203362577,"score_spread":0.2794665436729924,"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."}}