{"id":"W4404006113","doi":"10.23889/ijpds.v9i5.2936","title":"IPDLN Workshop: Opportunities for Cross-Country Comparisons of Linked Administrative Education and Health Data","year":2024,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Legal Education and Practice Innovations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Manitoba","funders":"","keywords":"Computer science; Data science; Business","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3880384,0.001354578,0.00127047,0.003458608,0.005162289,0.01333348,0.007607839,0.003859505,0.03416744],"category_scores_gemma":[0.2360405,0.001457549,0.003176366,0.003605586,0.003379346,0.01478075,0.04082162,0.01111652,0.00498766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006117995,"about_ca_system_score_gemma":0.02215701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004627543,"about_ca_topic_score_gemma":0.008442389,"domain_scores_codex":[0.7753451,0.1993113,0.006115862,0.005520138,0.007737421,0.005970092],"domain_scores_gemma":[0.6961728,0.2051497,0.009011593,0.04006965,0.02998401,0.01961221],"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":[0.001642781,0.001622845,0.01169613,0.005567479,0.0006971147,0.003043783,0.0966852,0.002299486,0.004181454,0.06416917,0.3906324,0.4177622],"study_design_scores_gemma":[0.0004345129,0.000467818,0.01028065,0.007782064,0.0001501668,0.0005164614,0.05300746,0.001563988,0.002673442,0.05701824,0.8657702,0.0003350757],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.07179469,0.0101617,0.367197,0.3532813,0.03491364,0.02204197,0.0324006,0.003945569,0.1042635],"genre_scores_gemma":[0.2582303,0.005877365,0.5906393,0.03790146,0.004711663,0.04096229,0.02103346,0.003306065,0.03733798],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.3880384,"threshold_uncertainty_score":0.7546576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6097572420545042,"score_gpt":0.6301518757336448,"score_spread":0.02039463367914063,"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."}}