{"id":"W2889191855","doi":"10.23889/ijpds.v3i1.697","title":"The International Population Data Linkage Network – Banff and Beyond","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; University of Calgary","funders":"","keywords":"Context (archaeology); Population; NOMINATE; Public relations; Library science; Computer science; Political science; Sociology; Geography","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":[],"category_scores_codex":[0.02014069,0.0001468125,0.000152019,0.0003403277,0.0019856,0.005512965,0.01439512,0.00004721017,0.0001436178],"category_scores_gemma":[0.01116711,0.00009935734,0.00004037863,0.0005932107,0.0005228263,0.008836553,0.005591672,0.0001829574,0.00006691282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001157998,"about_ca_system_score_gemma":0.0001073195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002591896,"about_ca_topic_score_gemma":0.001356863,"domain_scores_codex":[0.9938445,0.0001235153,0.001050458,0.0009363923,0.003687006,0.0003581217],"domain_scores_gemma":[0.9945568,0.001048,0.000806346,0.002039322,0.00137387,0.0001756214],"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":[0.0002042508,0.00006008197,0.04024966,0.000001903848,0.00009636379,0.000005542727,0.0001571358,0.0003535382,0.00007297521,0.1660067,0.2981852,0.4946066],"study_design_scores_gemma":[0.0003788135,0.00004016032,0.1216398,0.00001923571,0.00001518727,0.00004611178,0.0002130273,0.1569355,0.000005044609,0.0919166,0.6286447,0.0001458234],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1822985,0.0007341973,0.5136375,0.1415755,0.1362499,0.002212145,0.01016882,0.0002323934,0.01289095],"genre_scores_gemma":[0.9638779,0.0002471759,0.02255323,0.002372056,0.0055787,0.000006842343,0.003661908,0.00001615542,0.001685992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7815794,"threshold_uncertainty_score":0.9993137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2904191600282434,"score_gpt":0.5082813043779627,"score_spread":0.2178621443497193,"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."}}