{"id":"W2388285274","doi":"","title":"The Application and Study of ZigBee Network based on Electronic Nose","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Wireless Sensor Networks and IoT","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Router; Protocol (science); Electronic nose; Air quality index; Ventilation (architecture); Wireless sensor network; Computer network; Flooding (psychology); Embedded system; Real-time computing; Telecommunications; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007397561,0.0001060411,0.0001043204,0.00002673053,0.0001668316,0.00003194494,0.000147592,0.00003546908,9.122934e-7],"category_scores_gemma":[6.204014e-8,0.00008776056,0.00002424224,0.0002139326,0.00002582617,0.00001727764,0.00001818218,0.0001099266,0.000007591872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000027023,"about_ca_system_score_gemma":0.000006541662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002649693,"about_ca_topic_score_gemma":0.0001048572,"domain_scores_codex":[0.999347,0.00001512799,0.0001974557,0.0001595072,0.00007071064,0.0002102111],"domain_scores_gemma":[0.9995381,0.00009770403,0.0000388285,0.0002776393,0.00002625864,0.00002142727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006176462,0.0001928411,0.0008688447,0.00001318076,0.00002011457,1.026424e-7,0.00002951629,0.9101854,0.001566552,0.006443016,0.004319951,0.07635433],"study_design_scores_gemma":[0.0005251278,0.0000960039,0.01526163,0.000008609763,0.00002394595,0.000001570435,0.00001927163,0.6779969,0.000532994,0.001180602,0.3041692,0.0001840468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2493982,0.0006527358,0.7470233,0.0000988903,0.00001807422,0.001549996,0.000003571348,0.000208068,0.00104717],"genre_scores_gemma":[0.9968808,0.00002564627,0.002329228,0.00003142772,0.0002664903,0.0004122316,0.00001326937,0.00002148476,0.00001945959],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7474826,"threshold_uncertainty_score":0.3578772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001898109822760723,"score_gpt":0.175649517533937,"score_spread":0.1737514077111762,"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."}}