{"id":"W4403154564","doi":"10.1016/j.jss.2024.112233","title":"An empirical study of AI techniques in mobile applications","year":2024,"lang":"en","type":"article","venue":"Journal of Systems and Software","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"H2020 European Research Council; European Research Council; Horizon 2020 Framework Programme; Horizon 2020; Fonds National de la Recherche Luxembourg; European Commission","keywords":"Computer science","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":[0.0005369869,0.00005975293,0.0001931485,0.0002064988,0.00003868913,0.0001480909,0.0002597254,0.00003832555,1.907331e-7],"category_scores_gemma":[0.000007728073,0.00004436081,0.00003028033,0.0002880875,0.00001131626,0.0003070919,0.00005334473,0.0001777353,5.438889e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002407348,"about_ca_system_score_gemma":0.00006452751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002919577,"about_ca_topic_score_gemma":0.000001775969,"domain_scores_codex":[0.9991741,0.00005739909,0.0004003964,0.0001163269,0.0001671309,0.00008470698],"domain_scores_gemma":[0.9995121,0.00007419993,0.0000977805,0.0001541665,0.0001099677,0.00005176797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001643031,0.00172509,0.4557007,0.001035046,0.0001170659,0.00035581,0.03714943,0.0006957664,0.000701316,0.0007764777,0.008475965,0.4932509],"study_design_scores_gemma":[0.003994924,0.02513446,0.220523,0.008995909,0.0002329611,0.005600896,0.01945994,0.1934478,0.001831479,0.01227291,0.5060432,0.002462492],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5633731,0.002732164,0.4324645,0.00004902898,0.001018607,0.0002807832,2.192568e-7,0.00006089363,0.00002066911],"genre_scores_gemma":[0.9955317,0.00001327844,0.003830718,0.00001482093,0.0005780652,0.00001480885,1.07885e-7,0.000004669771,0.00001178385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4975672,"threshold_uncertainty_score":0.1808981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0186154426998529,"score_gpt":0.3315968903958141,"score_spread":0.3129814476959613,"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."}}