{"id":"W4319150660","doi":"10.1145/3526073.3527593","title":"Challenges in machine learning application development","year":2022,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); Concordia University; Polytechnique Montréal","funders":"","keywords":"Computer science; Workflow; Business process; Workbench; Database transaction; Process (computing); Suite; Server; Process management; Software engineering; Business process management; Software; Point (geometry); Engineering management; World Wide Web; Database; Artificial intelligence; Work in process; Business; Marketing; Engineering; 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":[0.04421406,0.0006311547,0.0009986374,0.002501968,0.002079445,0.007514083,0.004854178,0.003499998,0.002058213],"category_scores_gemma":[0.1106381,0.00102019,0.0008219061,0.00290605,0.004069885,0.01177381,0.004667641,0.005498515,0.002313883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00265567,"about_ca_system_score_gemma":0.006203935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002997014,"about_ca_topic_score_gemma":0.002472382,"domain_scores_codex":[0.9672538,0.01601647,0.002487783,0.003069375,0.01019441,0.000978185],"domain_scores_gemma":[0.797805,0.1541613,0.00471214,0.0108868,0.02935821,0.003076612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009294024,0.0004609605,0.01118366,0.001850907,0.0001130611,0.0006191273,0.00481853,0.02689173,0.004157687,0.07323129,0.02396769,0.8526124],"study_design_scores_gemma":[0.00008017374,0.0003012515,0.007188816,0.001272052,0.00005986051,0.002118598,0.00756769,0.2563591,0.011755,0.375137,0.337992,0.0001684608],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.06826972,0.01806152,0.7637872,0.1113028,0.0009453659,0.0009356585,0.0003443962,0.002894671,0.0334587],"genre_scores_gemma":[0.2351661,0.006285113,0.7474171,0.003556886,0.0004713524,0.0005885486,0.0004645409,0.0004965742,0.005553799],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.04421406,"threshold_uncertainty_score":0.2338291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03699836737462323,"score_gpt":0.254108676520274,"score_spread":0.2171103091456507,"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."}}