{"id":"W4317602008","doi":"10.1145/3554976","title":"(Re)Use of Research Results (Is Rampant)","year":2023,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Pessimism; Reuse; Measure (data warehouse); Computer science; Software engineering; Data science; Software; Epistemology; Data mining; Programming language; Engineering; Philosophy","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","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.01740288,0.00004590891,0.0001266813,0.0004610909,0.0004420427,0.0001437238,0.05534422,0.00002540621,0.00003129067],"category_scores_gemma":[0.2482794,0.00002893842,0.00009240463,0.004773309,0.0007196803,0.0001439235,0.08119787,0.000166927,0.0003955929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001439164,"about_ca_system_score_gemma":0.00005745574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000230853,"about_ca_topic_score_gemma":0.0001074795,"domain_scores_codex":[0.9967009,0.0008096636,0.0006364801,0.0002781744,0.001408656,0.0001661308],"domain_scores_gemma":[0.8695687,0.01685511,0.0003583419,0.1121681,0.001003423,0.00004637312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000909357,0.00004384571,0.001222168,0.000002530447,0.000007524424,6.68503e-8,0.001223624,0.0001555096,0.0001217182,0.002007431,0.988933,0.006273434],"study_design_scores_gemma":[0.0002566135,0.00002361845,0.05992424,0.00009526701,0.000008844534,2.763514e-7,0.004064929,0.01282815,0.001392915,0.2438335,0.6774996,0.0000720378],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.449678,0.0003714416,0.0000857636,0.5128102,0.001064638,0.0007879903,0.0005706491,0.0001491942,0.0344822],"genre_scores_gemma":[0.9743901,0.0001168044,0.01420498,0.0000860984,0.00001020471,0.000006727423,0.00001745484,0.000004640045,0.01116303],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5247121,"threshold_uncertainty_score":0.9497668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.815049139541793,"score_gpt":0.5777762256543041,"score_spread":0.2372729138874889,"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."}}