{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002122695,0.00003814404,0.00003933145,0.00007952339,0.0001802438,0.00001169886,0.0002951356,0.000009418386,0.00002960499],"category_scores_gemma":[0.000001690515,0.00003987147,0.00001037993,0.0002450304,0.000003436404,0.00005950597,0.0002591805,0.000115828,0.00001855488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000624493,"about_ca_system_score_gemma":0.00001742496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002122829,"about_ca_topic_score_gemma":0.00004988681,"domain_scores_codex":[0.9995072,0.00002540293,0.0001007992,0.0001908658,0.00009744504,0.00007825324],"domain_scores_gemma":[0.9997674,0.00001165759,0.00003067383,0.0001653364,0.000008152391,0.00001678395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[4.455704e-7,0.00003875965,0.0005400684,0.000001372756,8.326095e-7,3.501613e-7,0.000273318,0.00020472,0.0002683918,0.1766235,0.00001481813,0.8220334],"study_design_scores_gemma":[0.00009179152,0.00004101088,0.009586682,8.374913e-7,3.150763e-7,0.00001248373,0.0001525243,0.07879498,0.00331354,0.002919238,0.9049593,0.000127306],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001463303,0.0003399976,0.9744625,0.001999239,0.00001340054,0.0001440536,8.811869e-8,0.0003813134,0.02119607],"genre_scores_gemma":[0.9503825,0.00008466994,0.04824653,0.00008354199,0.000004383852,0.0006316581,0.000002081015,0.000002999947,0.0005616651],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9489192,"threshold_uncertainty_score":0.1625911,"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."}}