{"id":"W2295333720","doi":"10.14778/2856318.2856331","title":"CLAMShell","year":2015,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Crowds; Computer science; Latency (audio); Speedup; Data science; Computer security; Operating system; Telecommunications","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":[0.003006275,0.001522345,0.001225126,0.001990034,0.002056809,0.002648711,0.003330321,0.001779597,0.049664],"category_scores_gemma":[0.01334266,0.001311133,0.001193749,0.001545354,0.00119094,0.004849966,0.007501988,0.002117031,0.03711115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001151809,"about_ca_system_score_gemma":0.002268356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005478106,"about_ca_topic_score_gemma":0.01005936,"domain_scores_codex":[0.9967073,0.0004724255,0.0001878134,0.001230113,0.00115412,0.0002482667],"domain_scores_gemma":[0.9921828,0.001933801,0.0002972827,0.004096981,0.0009854393,0.0005036591],"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":[0.001734623,0.0002820398,0.003504734,0.0009413527,0.0002140784,0.0004339255,0.001384851,0.006531361,0.02095292,0.02050384,0.5526616,0.3908547],"study_design_scores_gemma":[0.0002725169,0.0002344999,0.003126406,0.0001809245,0.00006201925,0.0005436103,0.0004005893,0.1172033,0.02604946,0.04810256,0.8036551,0.0001690217],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"other","genre_scores_codex":[0.02048208,0.001355996,0.4227776,0.002683582,0.001334631,0.001531135,0.01661191,0.466773,0.06645007],"genre_scores_gemma":[0.2139088,0.0009475247,0.5962886,0.003389109,0.0005609173,0.001966197,0.0450727,0.04183712,0.09602903],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.049664,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02041225764979892,"score_gpt":0.2083040614978376,"score_spread":0.1878918038480387,"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."}}