{"id":"W2597503483","doi":"10.1109/saner.2017.7884643","title":"An exploratory study on library aging by monitoring client usage in a software ecosystem","year":2017,"lang":"en","type":"article","venue":"","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Japan Society for the Promotion of Science","keywords":"Leverage (statistics); Computer science; Software; Ecosystem; World Wide Web; Code (set theory); Data science; Operating system; Ecology","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009526709,0.0001522216,0.0002339698,0.0002063817,0.0004440969,0.001353082,0.002392702,0.00005084617,0.00001561787],"category_scores_gemma":[0.000141625,0.0001295185,0.00006365255,0.00024191,0.00002509634,0.002737578,0.000689349,0.0002581194,0.00007563431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006769718,"about_ca_system_score_gemma":0.00006894205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006827283,"about_ca_topic_score_gemma":0.00006220332,"domain_scores_codex":[0.9977732,0.0003370437,0.0002825794,0.0006774779,0.0005608262,0.000368848],"domain_scores_gemma":[0.9974735,0.0002042992,0.00008699948,0.002013582,0.00003425991,0.0001872961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000471316,0.0007042678,0.9714119,0.00001720719,0.00001438254,0.00006787169,0.001902173,0.0001346233,0.00009144288,0.00008264164,0.0001516022,0.02541718],"study_design_scores_gemma":[0.003167494,0.002209008,0.8887287,0.0006084563,0.00001967999,0.000004822031,0.01243295,0.06708551,0.01965059,0.001303388,0.003095905,0.001693438],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762539,0.0000524929,0.02239041,0.0002362344,0.0001844517,0.0002654451,0.000002578896,0.0003235984,0.0002909076],"genre_scores_gemma":[0.9974695,0.00001497646,0.002182595,0.00003473313,0.00007341128,0.00005603979,0.000001113771,0.00001269768,0.0001549364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08268314,"threshold_uncertainty_score":0.9996836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0409794645603257,"score_gpt":0.326629858966296,"score_spread":0.2856503944059703,"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."}}