{"id":"W6949763089","doi":"10.5281/zenodo.3588525","title":"Microservices: A Performance Tester's Dream or Nightmare? - Replication package","year":2019,"lang":"en","type":"other","venue":"Figshare","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Queen's University","funders":"","keywords":"Microservices; Scripting language; Automation; Replication (statistics); Software; Point (geometry); Software performance testing","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001373596,0.0002217874,0.0002269832,0.0001326794,0.0002581831,0.0002072988,0.001104724,0.0005204098,0.2761154],"category_scores_gemma":[0.0008809413,0.0001955761,0.00006454249,0.0002999642,0.00001956572,0.0003081758,0.0003163166,0.0002482415,0.02193586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205179,"about_ca_system_score_gemma":0.0003075811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001504118,"about_ca_topic_score_gemma":0.005304457,"domain_scores_codex":[0.9984759,0.00009452154,0.0001759461,0.0005768476,0.0003405833,0.0003361861],"domain_scores_gemma":[0.998016,0.00005595811,0.0003286451,0.001413105,0.00008472401,0.0001015431],"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":[0.00000798576,0.00002471843,0.0000333321,0.0004884339,0.00001156724,0.000001769827,0.0007024608,2.915323e-8,0.000005964126,0.00001152808,0.9957231,0.002989157],"study_design_scores_gemma":[0.0001427284,0.00003636167,0.0002322835,0.002007411,0.00000946846,0.000001782833,0.0001508288,0.000009047395,0.00006286363,0.00002405496,0.9970337,0.0002894347],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00002178128,0.0006636838,0.000001518189,0.0002752844,0.0003211705,0.001449871,0.2139212,0.0005998698,0.7827456],"genre_scores_gemma":[0.0006874765,0.000200264,0.000106996,0.0004516083,0.001619563,0.0004442283,0.1926039,0.0002477614,0.8036382],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2541795,"threshold_uncertainty_score":0.9788257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05010193129510802,"score_gpt":0.309471852889387,"score_spread":0.259369921594279,"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."}}