{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002586968,0.0002967516,0.0001747888,0.0002026514,0.0002402971,0.0005709491,0.0004685464,0.0003415102,0.001134569],"category_scores_gemma":[0.001016625,0.0001645745,0.0001624643,0.0001049615,0.0003989508,0.0005921128,0.0004473448,0.0002321543,0.0003372223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001751003,"about_ca_system_score_gemma":0.0003155891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006231356,"about_ca_topic_score_gemma":0.0007388744,"domain_scores_codex":[0.9997969,0.00004000211,0.00001385482,0.00004945493,0.00008067712,0.00001913737],"domain_scores_gemma":[0.9997038,0.00008422291,0.00003894983,0.00005535502,0.00009725435,0.00002035621],"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":[0.0002126361,0.0002204746,0.005080438,0.0003926347,0.00006503832,0.0006974323,0.0008306433,0.2776771,0.4246801,0.01392659,0.001969489,0.2742475],"study_design_scores_gemma":[0.00005957868,0.00147327,0.006545975,0.00009957627,0.0001131472,0.0007849053,0.0004696212,0.8338244,0.1049798,0.009071808,0.04252129,0.00005666282],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1503955,0.0002864048,0.8369009,0.0002740686,0.0001229859,0.0001779593,0.00005512071,0.001002896,0.01078418],"genre_scores_gemma":[0.8822713,0.0002729844,0.111243,0.000107719,0.00002283892,0.0001182551,0.00005762353,0.00006500101,0.005841172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001134569,"threshold_uncertainty_score":0.003795505,"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."}}