{"id":"W4366967224","doi":"10.1145/3544793.3560377","title":"10th International Workshop on Human Activity Sensing Corpus and Applications (HASCA)","year":2022,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Activity recognition; Computer science; Context (archaeology); Wearable computer; Scale (ratio); Human–computer interaction; Data science; Ubiquitous computing; Artificial intelligence; Embedded system","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":[0.01295409,0.002455792,0.003037169,0.006332419,0.001793458,0.006250496,0.004550015,0.00272609,0.04877468],"category_scores_gemma":[0.01997076,0.001177037,0.002742674,0.003778015,0.001433749,0.006417385,0.007104493,0.003928703,0.03640872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001827094,"about_ca_system_score_gemma":0.006264578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01926848,"about_ca_topic_score_gemma":0.02693137,"domain_scores_codex":[0.9936118,0.002436482,0.0006435539,0.00130664,0.001553307,0.0004483103],"domain_scores_gemma":[0.987163,0.002850109,0.0002123315,0.003625292,0.004831704,0.001317699],"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":[0.0004659015,0.0003251808,0.001451854,0.0006874443,0.0001447482,0.0001844001,0.00032094,0.001720954,0.006310171,0.007677525,0.5582926,0.4224182],"study_design_scores_gemma":[0.00008041115,0.0002056806,0.00632114,0.0007092572,0.00010224,0.0004858185,0.000520091,0.0222094,0.007014753,0.01848376,0.9437551,0.000112346],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01556526,0.04478752,0.656549,0.0196775,0.04136547,0.003443938,0.09244501,0.0572425,0.06892382],"genre_scores_gemma":[0.06124441,0.01669644,0.4560414,0.005289544,0.005865157,0.005417283,0.292339,0.007462982,0.1496437],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04877468,"threshold_uncertainty_score":0.1631676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05760376822005382,"score_gpt":0.310027879039066,"score_spread":0.2524241108190122,"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."}}