{"id":"W2164768240","doi":"10.1109/sahcn.2011.5984880","title":"OppSense: Information sharing for mobile phones in sensing field with data repositories","year":2011,"lang":"en","type":"article","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"VINNOVA","keywords":"Computer science; Data exchange; Overhead (engineering); Information exchange; Software deployment; Mobile phone; Mobile device; Wireless; Key (lock); Mobile computing; Computer network; Field (mathematics); Distributed computing; Database; Computer security; World Wide Web; Telecommunications; Operating 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":[0.001355514,0.0005941483,0.0009091967,0.0008865108,0.001048907,0.000997924,0.00233323,0.000900557,0.001266777],"category_scores_gemma":[0.004732799,0.0003878207,0.0004666879,0.0009775334,0.0007259121,0.002829407,0.003329242,0.000508782,0.0002741111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005089581,"about_ca_system_score_gemma":0.001017065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00131239,"about_ca_topic_score_gemma":0.001883985,"domain_scores_codex":[0.998974,0.0003029093,0.00008355204,0.0001656787,0.0003369052,0.0001369298],"domain_scores_gemma":[0.9975374,0.0009844598,0.0003355613,0.0006481835,0.0002728529,0.0002215004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001624306,0.0009022746,0.01236886,0.0006302184,0.0002771926,0.002184974,0.001934195,0.315812,0.07883082,0.04674831,0.007914011,0.5307729],"study_design_scores_gemma":[0.0001159049,0.0007046741,0.001658011,0.00002478275,0.00005927834,0.001313075,0.0003824896,0.951372,0.01992012,0.01389772,0.01048419,0.00006774694],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1181907,0.0002823084,0.8765949,0.0003316716,0.00004075491,0.0003011888,0.00009592262,0.001403844,0.002758641],"genre_scores_gemma":[0.84885,0.0001453138,0.1488222,0.0001020819,0.00002968296,0.0002827902,0.0001325138,0.00004747342,0.001587982],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00233323,"threshold_uncertainty_score":0.00716871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06031251944272874,"score_gpt":0.2546238503195334,"score_spread":0.1943113308768047,"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."}}