{"id":"W2576407273","doi":"","title":"Extracting Generalizable Spatial Features from Smart Phones Datasets.","year":2016,"lang":"en","type":"article","venue":"Constellation (Université du Québec à Chicoutimi)","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Wearable computer; Home automation; Focus (optics); Global Positioning System; Smart phone; Human–computer interaction; Scale (ratio); Smart environment; Wearable technology; Activity recognition; Smartwatch; Internet of Things; Data science; Artificial intelligence; Computer security; Telecommunications; Embedded system; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004584953,0.001022823,0.0008298181,0.003611486,0.0004088285,0.0009126868,0.001190429,0.001010802,0.001374333],"category_scores_gemma":[0.002665271,0.0002308058,0.001272229,0.00439852,0.0002611542,0.001232698,0.001004528,0.0006816757,0.002508012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005942567,"about_ca_system_score_gemma":0.0009779559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0204837,"about_ca_topic_score_gemma":0.05231353,"domain_scores_codex":[0.9992473,0.00008926664,0.00009525158,0.0002728828,0.0001812233,0.0001140558],"domain_scores_gemma":[0.99901,0.0001743695,0.0001291063,0.0003637099,0.0002664021,0.00005640009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005596754,0.0007451995,0.1256688,0.001473766,0.0007136359,0.001333364,0.0004775084,0.02712313,0.03100367,0.00280024,0.09932145,0.7087796],"study_design_scores_gemma":[0.0001122527,0.0006128686,0.3542832,0.0004471032,0.0003368472,0.002619756,0.00356186,0.4305329,0.03224788,0.01334657,0.1617509,0.0001479255],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4047653,0.005902857,0.2061246,0.001993015,0.0006478841,0.001244495,0.3505542,0.016295,0.01247264],"genre_scores_gemma":[0.4405779,0.00123688,0.140591,0.0002992319,0.0001677088,0.0006240063,0.4124871,0.0001616309,0.003854562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0204837,"threshold_uncertainty_score":0.04072893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506845301487688,"score_gpt":0.1971885191483976,"score_spread":0.1821200661335207,"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."}}