{"id":"W7042247180","doi":"","title":"Overview of supervisory control and data acquisition (SCADA)","year":2020,"lang":"en","type":"article","venue":"Digital Collections of Colorado (Colorado State University)","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Iran Telecommunication Research Center","keywords":"SCADA; Supervisory control; Data acquisition; Control (management); Control system; Data collection","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001003444,0.0001631723,0.0003646738,0.0004237484,0.0001749119,0.00004592129,0.0003322549,0.0001115465,0.0003660231],"category_scores_gemma":[0.00005906837,0.0001912489,0.00008924202,0.00151924,0.0002532816,0.0007540826,0.0001792916,0.000142472,0.0000257174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004199852,"about_ca_system_score_gemma":0.0001029376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005060041,"about_ca_topic_score_gemma":0.00005465111,"domain_scores_codex":[0.9987746,0.000129718,0.0003090268,0.0004127619,0.0001757447,0.0001981154],"domain_scores_gemma":[0.9988562,0.0001611104,0.0002246372,0.0003360889,0.0002522067,0.0001697479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.05177683,0.01791588,0.07684863,0.005074218,0.01250956,0.001276705,0.04060041,0.001127336,0.02075917,0.1742697,0.4303025,0.167539],"study_design_scores_gemma":[0.0418236,0.01354674,0.08875219,0.0005417469,0.001875974,0.0001676267,0.03952061,0.007551268,0.001833142,0.004395631,0.7973186,0.002672819],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.835349,0.0007539009,0.009090697,0.002379899,0.0004541356,0.001355448,0.005833084,0.0002366968,0.1445471],"genre_scores_gemma":[0.9960149,0.0002646157,0.000108304,0.0002232871,0.00002536091,0.000001779138,0.0001916569,0.00001798227,0.003152094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3670161,"threshold_uncertainty_score":0.7798902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09154990656507844,"score_gpt":0.2762372742837964,"score_spread":0.1846873677187179,"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."}}