{"id":"W4402405797","doi":"10.23889/ijpds.v9i5.2715","title":"Using linked data to inform multidimensional real-world issues: Canadian examples","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Computer science; Data science","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":[0.06402529,0.0009690181,0.000736217,0.009678284,0.0194427,0.01796538,0.003849581,0.004230903,0.005105003],"category_scores_gemma":[0.09173937,0.0008267877,0.001731898,0.0428711,0.01144975,0.009835009,0.011809,0.005672011,0.0007798381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09763438,"about_ca_system_score_gemma":0.1389195,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9589664,"about_ca_topic_score_gemma":0.9733908,"domain_scores_codex":[0.95232,0.0241765,0.002798288,0.00213288,0.01519551,0.00337681],"domain_scores_gemma":[0.8844796,0.05167842,0.002282917,0.009483949,0.04873635,0.003338677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002073703,0.00009872777,0.01974359,0.002728704,0.0001674393,0.002956994,0.1175436,0.00359077,0.0008726279,0.4632352,0.1640628,0.2247922],"study_design_scores_gemma":[0.00004135943,0.00002301718,0.006602949,0.002209543,0.00006518391,0.0003688998,0.04237771,0.001752645,0.0004022211,0.02677276,0.9192406,0.0001431711],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06206058,0.05017686,0.1109105,0.3650178,0.0036079,0.002048098,0.01836518,0.000737896,0.3870752],"genre_scores_gemma":[0.4904467,0.1124352,0.2804166,0.03057184,0.001115829,0.001919467,0.01668619,0.001134395,0.06527381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09763438,"threshold_uncertainty_score":0.7083903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3328900414847326,"score_gpt":0.5023358135751167,"score_spread":0.1694457720903841,"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."}}