{"id":"W3126482160","doi":"","title":"Adaptive Engineering of an Embedded System, Engineered for use by Search and Rescue Canines","year":2011,"lang":"en","type":"article","venue":"SOURCE Sheridan's Institutional Repository (Sheridan College)","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Computer science; Engineering","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":[0.0005133586,0.0003946305,0.0005427235,0.0002456878,0.0004724639,0.0001763105,0.000683697,0.0002080568,0.000004099385],"category_scores_gemma":[0.00010777,0.0004177275,0.0001623495,0.0004550165,0.0002339837,0.001638928,0.0002177547,0.0002363422,0.000002976503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003151002,"about_ca_system_score_gemma":0.0004840202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00145446,"about_ca_topic_score_gemma":0.00007347202,"domain_scores_codex":[0.9972749,0.0001900204,0.0006828143,0.0008003108,0.0005857363,0.0004661714],"domain_scores_gemma":[0.9979596,0.0002543741,0.0001474072,0.0006975866,0.0005993923,0.0003416758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004304935,0.003059504,0.005737399,0.004948791,0.003517223,0.001535387,0.03240206,0.06508907,0.5912647,0.2575491,0.002914993,0.02767684],"study_design_scores_gemma":[0.003021157,0.001245257,0.005008926,0.0008056576,0.0001027607,0.001914336,0.002939027,0.8558607,0.1219126,0.00004008474,0.005641146,0.001508291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.605544,0.0001497697,0.3916465,0.00001421353,0.0007853359,0.0008454078,0.0001669757,0.0003287984,0.0005189626],"genre_scores_gemma":[0.9612964,0.000001955969,0.03762435,0.00001917972,0.000193795,0.0002211888,0.00001589897,0.00004367911,0.0005835933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7907717,"threshold_uncertainty_score":0.9998274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02898453247642244,"score_gpt":0.212431096121689,"score_spread":0.1834465636452666,"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."}}