{"id":"W1989707041","doi":"10.2166/wst.2014.057","title":"Instrumentation, control and automation in wastewater – from London 1973 to Narbonne 2013","year":2014,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canada Research Chairs","keywords":"Instrumentation (computer programming); Automation; Control (management); Systems engineering; Key (lock); Computer science; Control system; Wastewater; Automatic control; Engineering; Control engineering; Waste management; Electrical engineering; Computer security; Artificial intelligence; Operating system; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006953145,0.0001597342,0.0001886768,0.0006170598,0.0001639256,0.0000845153,0.0007835717,0.0001539202,0.00005111165],"category_scores_gemma":[0.000108229,0.0001186818,0.0000123047,0.0008528371,0.001143725,0.0005338124,0.0007762009,0.0001540334,0.0004953813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002187097,"about_ca_system_score_gemma":0.000005760832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001485625,"about_ca_topic_score_gemma":0.0002645013,"domain_scores_codex":[0.9981607,0.0000411603,0.0002869086,0.0006402591,0.0003150102,0.0005559371],"domain_scores_gemma":[0.9993222,0.00002096576,0.00004822882,0.0005222738,0.00001334699,0.00007303597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009037842,0.00003531337,0.184931,0.000002303219,0.000001771317,0.00000260483,0.001108082,0.0003941208,0.799432,0.0002991297,0.00007407101,0.01371058],"study_design_scores_gemma":[0.0006350262,0.0001864743,0.08059622,0.00001794667,0.000004350552,0.000006806974,0.0002618186,0.002969976,0.8875911,0.02458686,0.002888035,0.0002554014],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829863,0.000006048361,0.001296703,0.01469809,0.0001966859,0.0002833012,0.000002088648,0.0004310745,0.00009966828],"genre_scores_gemma":[0.9917839,0.000003328731,0.007898137,0.000172476,0.00001485702,0.00007246843,0.000002138653,0.00000904095,0.00004361132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1043347,"threshold_uncertainty_score":0.6367289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007077717792877455,"score_gpt":0.2225516537287717,"score_spread":0.2154739359358942,"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."}}