{"id":"W2073102918","doi":"10.1007/s11219-014-9238-2","title":"Studying the relationship between source code quality and mobile platform dependence","year":2014,"lang":"en","type":"article","venue":"Software Quality Journal","topic":"Software Engineering Research","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Queen's University","funders":"","keywords":"Android (operating system); Source code; Software quality; Computer science; Software quality assurance; Software; Operating system; Source lines of code; Mobile apps; Mobile device; Mobile computing; Quality assurance; Software development; World Wide Web; Engineering","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01214387,0.0002107183,0.0003140349,0.0001368621,0.001114433,0.0007361775,0.0015282,0.0001250575,0.000009643602],"category_scores_gemma":[0.01872822,0.0001578252,0.0001074707,0.0004499736,0.0001570918,0.0008166383,0.0005503035,0.001333142,0.00003478362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001329685,"about_ca_system_score_gemma":0.0001386133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006892381,"about_ca_topic_score_gemma":0.00001527295,"domain_scores_codex":[0.9962265,0.0008819788,0.0007230911,0.0004175711,0.00119776,0.0005530662],"domain_scores_gemma":[0.9720845,0.02597571,0.0003355311,0.0009799869,0.0002565739,0.0003676935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004837506,0.00001798618,0.9512967,0.00003761096,0.00002340327,0.000002215851,0.002323008,0.0004078469,0.000007401459,0.003308408,0.0001216236,0.04244892],"study_design_scores_gemma":[0.0003848453,0.000086572,0.9800092,0.00004872838,0.000008195246,0.0000938964,0.0002168739,0.0004189464,0.00003428009,0.0169165,0.001538271,0.0002437078],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4581633,0.0001588804,0.5408065,0.0003932184,0.0001440566,0.0001186968,0.000003088492,0.0002013137,0.00001092604],"genre_scores_gemma":[0.9752296,0.000008575184,0.02412532,0.0001579686,0.0003091562,0.00001905401,0.000001610452,0.00001994792,0.0001287775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5170663,"threshold_uncertainty_score":0.9895374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.152923259708518,"score_gpt":0.3828906023119051,"score_spread":0.2299673426033871,"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."}}