{"id":"W2754104704","doi":"10.1145/3131893","title":"TrailSense","year":2017,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Cluster analysis; Generalizability theory; Artificial intelligence; Crowdsensing; Climb; Data mining; Machine learning; Pattern recognition (psychology); Computer security; Statistics; Mathematics; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001226071,0.0001311393,0.0001650866,0.00009362234,0.0006081258,0.000258489,0.003880317,0.00009893281,0.000002110127],"category_scores_gemma":[0.0006283203,0.00008846205,0.00007363529,0.0001210101,0.0003232486,0.0005676601,0.002495087,0.0002677474,0.000005175004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002654453,"about_ca_system_score_gemma":0.00001048315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002578439,"about_ca_topic_score_gemma":0.000001481895,"domain_scores_codex":[0.9992064,0.000002676606,0.0001594307,0.000327916,0.0001313362,0.0001721874],"domain_scores_gemma":[0.9982321,0.00005923864,0.0003624526,0.00117782,0.0001504507,0.00001798028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006038738,0.0002405377,0.002541958,0.00006862522,0.00006703751,0.00000130865,0.000584189,0.000003024186,0.2508265,0.1494466,0.005168565,0.5909913],"study_design_scores_gemma":[0.00009701146,0.0003050235,0.002638271,0.0001122855,0.000006383961,0.00002088436,0.000682399,0.0002090894,0.890917,0.09993116,0.004959919,0.0001205463],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798316,0.0001279167,0.000739486,0.006901832,0.0001332439,0.0005328996,0.000003531133,0.0008605632,0.01086898],"genre_scores_gemma":[0.9938046,0.0002215158,0.005207709,0.00004617957,0.00001405098,0.0002534351,2.845655e-8,0.000007385236,0.0004450782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6400905,"threshold_uncertainty_score":0.7210658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0143219757470816,"score_gpt":0.2718296595039684,"score_spread":0.2575076837568868,"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."}}