{"id":"W2606501131","doi":"10.23889/ijpds.v1i1.76","title":"Social Data Linkage Environment","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Identifier; Record linkage; Computer science; Index (typography); Personally identifiable information; Internet privacy; Unique identifier; Database; World Wide Web; Computer security; Sociology; Demography","routes":{"ca_aff":true,"ca_fund":false,"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","sts","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.01529445,0.0001006736,0.0001401999,0.0002901348,0.002749281,0.006432106,0.03021718,0.00003328527,0.0002787277],"category_scores_gemma":[0.01013734,0.00008004458,0.00004608919,0.0000947729,0.0004193577,0.01384362,0.009070815,0.0001391163,0.0001999605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001021388,"about_ca_system_score_gemma":0.0001072068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001339696,"about_ca_topic_score_gemma":0.00008385495,"domain_scores_codex":[0.9943936,0.00006173865,0.0007040292,0.0008211129,0.003771907,0.0002475916],"domain_scores_gemma":[0.9946865,0.0002102001,0.001040686,0.003574878,0.0003582773,0.0001294883],"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":[0.00008495343,0.0001685401,0.0170147,0.000002990191,0.00006492607,0.0000219242,0.0002070194,0.0002071328,0.0002455777,0.09025483,0.233007,0.6587204],"study_design_scores_gemma":[0.0004346553,0.00001616038,0.1680013,0.00000936597,0.00001298635,0.00001895123,0.0001293479,0.03616186,0.00001502357,0.04554885,0.7495134,0.0001380514],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0686361,0.00008947932,0.7546564,0.1202116,0.02845367,0.001081569,0.01780304,0.0000806437,0.008987471],"genre_scores_gemma":[0.9817017,0.00005092724,0.01261764,0.0005534245,0.001563635,0.000003178749,0.00167624,0.000007821719,0.001825418],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9130656,"threshold_uncertainty_score":0.9999492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6447609076066653,"score_gpt":0.5948565105111473,"score_spread":0.04990439709551797,"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."}}