{"id":"W2594470044","doi":"","title":"Enabling devops for containerized data-intensive applications: an exploratory study","year":2016,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); York University","funders":"","keywords":"DevOps; Computer science; Container (type theory); Popularity; Process (computing); Software engineering; Software; Exploratory research; Cloud computing; Domain (mathematical analysis); Software development; Set (abstract data type); Data science; Systems engineering; Engineering; Software deployment; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004175789,0.000556864,0.000375947,0.0006390976,0.0007165287,0.001157185,0.001158394,0.0006193497,0.0007801626],"category_scores_gemma":[0.01150662,0.0003782632,0.000363579,0.0007221599,0.0008630974,0.001665497,0.001195271,0.001308465,0.0001904395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007903829,"about_ca_system_score_gemma":0.0008490074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002608455,"about_ca_topic_score_gemma":0.00268945,"domain_scores_codex":[0.9976755,0.001037619,0.0001434199,0.0002380578,0.0006020942,0.0003033129],"domain_scores_gemma":[0.9909118,0.004866587,0.0005889379,0.001545265,0.001477818,0.0006094074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.002141931,0.01527462,0.1006875,0.003341508,0.0002505991,0.004040856,0.02727883,0.165589,0.2374388,0.02379487,0.01230987,0.4078516],"study_design_scores_gemma":[0.0005588976,0.0128448,0.1244252,0.0004661354,0.0002406855,0.00147865,0.0239528,0.5495549,0.199444,0.007692207,0.07905344,0.0002883096],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874615,0.00009789325,0.00883977,0.0001433482,0.0000180227,0.0003330496,0.0001237094,0.0003601386,0.002622544],"genre_scores_gemma":[0.9684736,0.0002265521,0.02914119,0.00006427657,0.00001861449,0.0003085867,0.0003736079,0.0001599269,0.001233735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004175789,"threshold_uncertainty_score":0.02208394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03069328156966707,"score_gpt":0.2684469587739187,"score_spread":0.2377536772042516,"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."}}