{"id":"W2039233455","doi":"10.1145/2110363.2110394","title":"Human network data collection in the wild","year":2012,"lang":"en","type":"article","venue":"","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Data science; Context (archaeology); Scalability; Data collection; Aggregate (composite); Software deployment; Scope (computer science); Social network (sociolinguistics); Data aggregator; Wireless sensor network; World Wide Web; Social media","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002988695,0.00002871276,0.00004516786,0.00002320828,0.0007508434,0.00004679342,0.0003351312,0.00003224799,0.001024631],"category_scores_gemma":[0.0000838272,0.00002039477,0.00001629152,0.0005546227,0.00008228226,0.0002094935,0.00002272088,0.00006594701,0.00004570013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003668185,"about_ca_system_score_gemma":0.00004054641,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.039965,"about_ca_topic_score_gemma":0.26742,"domain_scores_codex":[0.9991437,0.0003418779,0.00008991714,0.00008533605,0.000163612,0.000175616],"domain_scores_gemma":[0.9995334,0.0001089277,0.00002095824,0.000293235,0.0000144295,0.00002910373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002460242,0.0002718765,0.5933971,0.000003639507,0.00001911492,2.335747e-7,0.03883897,0.0001910406,0.000002833631,0.1852991,0.1747223,0.00725128],"study_design_scores_gemma":[0.0002215667,0.00002393315,0.4400748,0.00001169717,0.00006667039,2.161367e-7,0.04462497,0.003090544,0.000002454906,0.007705907,0.5039412,0.0002360389],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3139148,0.0003026,0.004848593,0.01247835,0.0004087313,0.0006300004,0.000002367172,0.0001247259,0.6672899],"genre_scores_gemma":[0.9960465,0.000007757033,0.00005630689,0.0005930709,0.0005399123,0.00000792069,0.00001932285,0.00000140734,0.002727772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6821318,"threshold_uncertainty_score":0.9998885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09208324734735865,"score_gpt":0.3767651013521908,"score_spread":0.2846818540048321,"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."}}