{"id":"W2140743104","doi":"10.1109/tmech.2009.2012850","title":"An Electronic Nose Network System for Online Monitoring of Livestock Farm Odors","year":2009,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Electronic nose; Odor; Livestock; Computer science; Process (computing); Real-time computing; Artificial intelligence; Geography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006102716,0.0002972984,0.0003625744,0.0001219939,0.0001095175,0.00001464826,0.0003441161,0.0002702873,0.000003131718],"category_scores_gemma":[0.000005652346,0.0003204955,0.0001722899,0.0003397376,0.00003041489,0.0001369286,0.000001129161,0.0005556668,0.000004004426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005510316,"about_ca_system_score_gemma":0.00001694954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003015568,"about_ca_topic_score_gemma":0.00001302583,"domain_scores_codex":[0.9983993,0.00001405346,0.0003940536,0.0002992067,0.0001823511,0.0007111068],"domain_scores_gemma":[0.9991684,0.00008807904,0.00007261399,0.0005180083,0.00006278272,0.00009009061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004410128,0.0001011786,0.000002141507,0.00006919599,0.00004809226,7.076807e-7,0.00002452208,0.8119433,0.1553461,0.001255702,0.000004960932,0.03116003],"study_design_scores_gemma":[0.0006879879,0.0009798377,0.00001813035,0.0001585113,0.000101698,0.000008789369,0.0004098069,0.101325,0.8927431,0.002370231,0.0007605565,0.0004364016],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4314806,0.0004930171,0.565658,0.00003396831,0.0004202687,0.0003584601,0.00005906539,0.001476908,0.00001980803],"genre_scores_gemma":[0.9628682,0.0003769152,0.03644621,0.000006868632,0.0001562028,0.00004863858,0.00001064758,0.00006808918,0.00001826646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.737397,"threshold_uncertainty_score":0.9999247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076446270559765,"score_gpt":0.2469823075737417,"score_spread":0.2362178448681441,"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."}}