{"id":"W4312759888","doi":"10.1007/978-3-031-18872-5_17","title":"Low-Code Internet of Things Application Development for Edge Analytics","year":2022,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Science Foundation Ireland; European Commission","keywords":"Analytics; Computer science; Python (programming language); Software analytics; Software deployment; Data science; Software engineering; Internet of Things; World Wide Web; Software; Software development; Software development process; 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":[0.0006093084,0.0005865108,0.000177462,0.0007800906,0.0004886963,0.001974151,0.001146769,0.0007670442,0.01718178],"category_scores_gemma":[0.0020985,0.0003853494,0.0004916401,0.0007137096,0.0003576695,0.001355167,0.001380207,0.001445125,0.01396796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006273046,"about_ca_system_score_gemma":0.0009158633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000816402,"about_ca_topic_score_gemma":0.001313324,"domain_scores_codex":[0.9994636,0.00008802519,0.00002679322,0.0000744521,0.000309982,0.00003713228],"domain_scores_gemma":[0.9988845,0.0004936864,0.00004175557,0.0002104511,0.0002810455,0.00008859276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007110296,0.0003161586,0.001270251,0.0007200532,0.00001813787,0.001084695,0.001249109,0.009639958,0.04126918,0.1283895,0.1613752,0.6545967],"study_design_scores_gemma":[0.00002269166,0.00006801278,0.0009063651,0.0002933696,0.00001288233,0.001238849,0.00009425564,0.03238379,0.02257919,0.02518836,0.9171677,0.00004461638],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01021234,0.0007645395,0.8014932,0.001290706,0.0005315696,0.0005975851,0.0007246229,0.02019597,0.1641894],"genre_scores_gemma":[0.05232484,0.001575763,0.6848691,0.0009956604,0.0001538105,0.0008200365,0.003197144,0.01086982,0.245194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01718178,"threshold_uncertainty_score":0.05747879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01671228702148972,"score_gpt":0.2606784322276566,"score_spread":0.2439661452061669,"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."}}