{"id":"W3005609888","doi":"10.1515/em-2020-0033","title":"Sampling from networks: respondent-driven sampling","year":2021,"lang":"en","type":"preprint","venue":"Epidemiologic Methods","topic":"HIV, Drug Use, Sexual Risk","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; Toronto Metropolitan University; University of Toronto; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; McGill University Health Centre; University of Victoria; McGill University","funders":"Public Health Agency; Canadian Blood Services; Canadian Institutes of Health Research; Ministère de la Santé et des Services sociaux; Public Health Agency of Canada; Natural Sciences and Engineering Research Council of Canada; Ontario HIV Treatment Network; Canadian Foundation for AIDS Research","keywords":"Homophily; Sampling (signal processing); Respondent; Computer science; Population; Differential (mechanical device); Sample (material); Social network (sociolinguistics); Econometrics; Statistics; Mathematics; Psychology; Social psychology; Demography; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.01810502,0.001137444,0.004337534,0.0003560447,0.0002459048,0.0001184738,0.00101117,0.002537241,0.001449188],"category_scores_gemma":[0.06424387,0.0009712611,0.001079064,0.000521115,0.0002695262,0.0000877414,0.002877919,0.005419733,0.00008996128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005398585,"about_ca_system_score_gemma":0.0005487471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007897425,"about_ca_topic_score_gemma":0.00003592787,"domain_scores_codex":[0.9810695,0.011616,0.002585354,0.002810637,0.0005368892,0.001381623],"domain_scores_gemma":[0.9647171,0.02951762,0.001387443,0.003216775,0.0004016841,0.0007593313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001234172,0.0005418928,0.08485287,0.001018643,0.003252389,0.0007573781,0.007046238,0.3579139,0.02454515,0.0006961831,0.007986915,0.5101542],"study_design_scores_gemma":[0.005385112,0.001099983,0.2217101,0.01362941,0.006263316,0.000370964,0.03048603,0.4920769,0.003424676,0.1245214,0.09379347,0.007238673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1061461,0.01667034,0.8670944,0.001599632,0.004121989,0.001064471,0.00008639535,0.0006181178,0.002598546],"genre_scores_gemma":[0.01848499,0.003898901,0.9659682,0.004270641,0.003937236,0.0002214905,0.002033646,0.0001756599,0.00100926],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5029156,"threshold_uncertainty_score":0.9994636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3940505545443231,"score_gpt":0.532228469113377,"score_spread":0.1381779145690538,"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."}}