{"id":"W201096548","doi":"10.1023/a:1015777918028","title":"Guest Editorial: Revealing the spaces of urban health","year":2001,"lang":"en","type":"article","venue":"GeoJournal","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; University of Calgary","funders":"","keywords":"Human geography; Geography; Economic geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.006581757,0.003407721,0.003279625,0.004493394,0.002956261,0.006258207,0.003457947,0.01728144,0.0131052],"category_scores_gemma":[0.03640999,0.001244682,0.002538112,0.001973526,0.003030088,0.003272505,0.001667051,0.01673052,0.004606383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001862862,"about_ca_system_score_gemma":0.001622709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001362962,"about_ca_topic_score_gemma":0.003584382,"domain_scores_codex":[0.997232,0.0009227704,0.0003254845,0.0004794488,0.0008275973,0.0002126018],"domain_scores_gemma":[0.9731563,0.01619572,0.00122549,0.001025292,0.005829186,0.002567944],"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":[0.00003622877,0.000009109349,0.00004348692,0.0001151106,0.00002022542,0.0001645387,0.00001821912,0.00002656262,0.0000424529,0.0005425056,0.9971864,0.001795256],"study_design_scores_gemma":[0.0001451178,0.00006335939,0.001051282,0.0004924756,0.0002065205,0.0007018903,0.0001677553,0.000699845,0.0002711461,0.004510817,0.991649,0.0000408141],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00009369575,0.002302526,0.0002789013,0.08067814,0.9156111,0.0000141783,0.0001078608,0.00005158526,0.0008620794],"genre_scores_gemma":[0.001614375,0.001808024,0.0001916796,0.02633055,0.9647177,0.00002397454,0.00003935814,0.0000497174,0.005224672],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01728144,"threshold_uncertainty_score":0.04384118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1376821690655342,"score_gpt":0.4297950154069978,"score_spread":0.2921128463414635,"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."}}