{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01820126,0.0009942998,0.001212395,0.004748121,0.003486137,0.007002906,0.003860097,0.005015638,0.1048582],"category_scores_gemma":[0.03923144,0.0007115981,0.0006172839,0.00836569,0.002110059,0.006642768,0.006185423,0.006228035,0.06870843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007808519,"about_ca_system_score_gemma":0.03689774,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1065355,"about_ca_topic_score_gemma":0.07480353,"domain_scores_codex":[0.9892721,0.002804949,0.0006258043,0.001519601,0.004763405,0.001014102],"domain_scores_gemma":[0.9674031,0.007341734,0.00167444,0.003750215,0.01171742,0.008113135],"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":[0.0000260992,0.000007594055,0.0003117019,0.00006337847,0.000004301699,0.00001432248,0.00003320691,0.00002082013,0.00002945673,0.005056579,0.9444546,0.04997787],"study_design_scores_gemma":[0.000006733784,0.00000267617,0.0008811097,0.0002322794,0.000002249701,0.00001759967,0.00003477299,0.0000394193,0.00002668261,0.001941568,0.9968061,0.000008697982],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001017729,0.03558087,0.009071218,0.3511715,0.03370627,0.0005782719,0.07077661,0.00418022,0.4939173],"genre_scores_gemma":[0.01098711,0.03512078,0.03465582,0.1555732,0.01025131,0.00326541,0.1483647,0.003834797,0.5979468],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8934645,"threshold_uncertainty_score":0.3507855,"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."}}