{"id":"W4392463913","doi":"10.2139/ssrn.4748213","title":"A Prisma-Driven Bibliometric Analysis of the Scientific Literature on Assurance Case Patterns","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Safety Systems Engineering in Autonomy","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Management science; Data science; Computer science; Engineering ethics; 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":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","bibliometrics","research_integrity"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.001800787,0.0004778825,0.0006943032,0.05328574,0.0001308941,0.0005489682,0.0009637019,0.0003729025,0.00001246182],"category_scores_gemma":[0.00009214754,0.0003614397,0.0009620859,0.08591238,0.00004562446,0.00007214502,0.0003218659,0.007317304,0.00001676044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001981373,"about_ca_system_score_gemma":0.0011177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003330702,"about_ca_topic_score_gemma":0.0003599099,"domain_scores_codex":[0.9962944,0.0001083632,0.0007864093,0.0004897054,0.0007101058,0.001611],"domain_scores_gemma":[0.9982283,0.0001409042,0.0002717319,0.001064658,0.0001987504,0.00009571893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004922706,0.00002931293,0.001597191,0.0008670602,0.007124201,0.0002065868,0.0006195006,0.9820977,0.000253753,0.002063145,0.0002382154,0.004898398],"study_design_scores_gemma":[0.00101736,0.0002466538,0.03505988,0.00978802,0.009589534,0.01289829,0.0006138454,0.9050293,0.001449256,0.01602755,0.005469284,0.002811036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9460037,0.03341684,0.01268145,0.0001319826,0.006483105,0.0004227645,0.0002919914,0.0002640078,0.0003041658],"genre_scores_gemma":[0.9970878,0.00171587,0.00006625973,0.000005533122,0.0003442793,0.0000315475,0.00002434148,0.0001057386,0.0006185906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07706843,"threshold_uncertainty_score":0.9998838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007424877971936863,"score_gpt":0.227549766591476,"score_spread":0.2201248886195392,"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."}}