{"id":"W7011498392","doi":"","title":"From the Margins: Assessing Policy Approaches to Addressing Suburban Disadvantage in Toronto","year":2015,"lang":"en","type":"other","venue":"eScholarship@McGill (McGill)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Disadvantage; Public policy; Government (linguistics); Poverty; Inequality","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001989262,0.0003551683,0.0002893851,0.001103487,0.0043917,0.002977134,0.001127074,0.0009629055,0.006195432],"category_scores_gemma":[0.0113519,0.0002598557,0.0003662238,0.002419327,0.001948281,0.001517646,0.004327642,0.001139309,0.0002024772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0760719,"about_ca_system_score_gemma":0.111709,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9765515,"about_ca_topic_score_gemma":0.9928637,"domain_scores_codex":[0.9970366,0.000947287,0.00008494532,0.0001040799,0.0005680224,0.001259019],"domain_scores_gemma":[0.991863,0.001967466,0.001040726,0.0002280616,0.001580652,0.003320047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007678029,0.0004702213,0.6000739,0.001140967,0.0003080065,0.0006739037,0.06480248,0.02017622,0.0005820584,0.0644666,0.09118906,0.1553488],"study_design_scores_gemma":[0.00006090379,0.0003207233,0.7907912,0.0008805777,0.0001966124,0.00005425214,0.1495795,0.009939508,0.0005376409,0.006727607,0.0408365,0.00007503628],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9030421,0.002916363,0.0008591232,0.02383694,0.0001035216,0.0003776195,0.003930049,0.0000472799,0.06488699],"genre_scores_gemma":[0.9918723,0.001087305,0.0006058005,0.0005799351,0.00002056325,0.0001599926,0.0003639067,0.00001212037,0.005298153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0760719,"threshold_uncertainty_score":0.5519428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0996403609342555,"score_gpt":0.3173131599074968,"score_spread":0.2176727989732413,"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."}}