{"id":"W2082247991","doi":"10.1109/percomw.2013.6529488","title":"Sensor Mobile Enablement (SME): A light-weight standard for opportunistic sensing services","year":2013,"lang":"en","type":"article","venue":"","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Ontario Council on Graduate Studies, Council of Ontario Universities","keywords":"Interoperability; Computer science; Mobile device; Android (operating system); Coding (social sciences); Mobile computing; Mobile telephony; Computer network; World Wide Web; Mobile radio; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004136315,0.001082124,0.000874448,0.001962038,0.001028407,0.003132923,0.002198356,0.002659617,0.002877281],"category_scores_gemma":[0.01071167,0.0006491084,0.0008354596,0.001189521,0.001886602,0.004298345,0.005747556,0.003411672,0.001805134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001762,"about_ca_system_score_gemma":0.001465759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008890121,"about_ca_topic_score_gemma":0.00095641,"domain_scores_codex":[0.9948296,0.001163054,0.0006619889,0.0006409044,0.002176118,0.0005283824],"domain_scores_gemma":[0.9936851,0.001485973,0.0008409398,0.002161413,0.001446564,0.0003799754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001597259,0.0004950687,0.004322407,0.002723715,0.0001803655,0.001366951,0.001899915,0.01148381,0.1312503,0.4531456,0.03852145,0.3530131],"study_design_scores_gemma":[0.0002209183,0.001700944,0.006490614,0.001338958,0.0002982364,0.003977403,0.0006990129,0.08916017,0.1540181,0.09869106,0.6428746,0.0005300251],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03234578,0.004175649,0.9080576,0.00339896,0.001335805,0.001223769,0.001324972,0.01493556,0.03320197],"genre_scores_gemma":[0.630206,0.004940711,0.3206201,0.00413324,0.0009827038,0.003252724,0.002786036,0.001592081,0.03148631],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004136315,"threshold_uncertainty_score":0.02187514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009740589626307085,"score_gpt":0.2267921661279509,"score_spread":0.2170515765016438,"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."}}