{"id":"W2891745186","doi":"10.23889/ijpds.v3i4.715","title":"The Canadian Urban Environmental Health Research Consortium (CANUE): a national data linkage initiative","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Victoria; McGill University Health Centre","funders":"","keywords":"Data sharing; Environmental data; Biobank; Geospatial analysis; Metadata; Confidentiality; Data science; Environmental resource management; Environmental health; Business; Environmental planning; Geography; Computer science; Political science; Medicine; World Wide Web; Environmental 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":"codex-gemma-dda1882f352a","candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.01750191,0.0001523246,0.0001158918,0.0003121525,0.005864227,0.0008155745,0.005621052,0.00005696502,0.0005802679],"category_scores_gemma":[0.003676794,0.000128082,0.00002709646,0.000453028,0.002484473,0.003733494,0.002137884,0.0005605025,0.0004423987],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00398679,"about_ca_system_score_gemma":0.001409553,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02534261,"about_ca_topic_score_gemma":0.1573022,"domain_scores_codex":[0.9937135,0.0003341373,0.000612491,0.0009863947,0.003480719,0.0008727317],"domain_scores_gemma":[0.9971931,0.0005334583,0.0003898414,0.001048134,0.0001980883,0.0006373733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002272953,0.0003757822,0.4157868,0.000008615908,0.0001541341,0.00004177257,0.003575743,0.0004511239,0.001527832,0.009672127,0.3467831,0.2213957],"study_design_scores_gemma":[0.0004803813,0.0001302419,0.4180608,0.00003573433,0.000005094329,0.00009952398,0.0004141633,0.0459431,0.00005886553,0.003878559,0.5306768,0.0002167787],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6469719,0.0007854197,0.02950685,0.202284,0.02369164,0.00894131,0.04034803,0.0001964577,0.04727434],"genre_scores_gemma":[0.9914324,0.0001343721,0.002945876,0.002815196,0.0009854673,0.00001695258,0.001384407,0.00001857529,0.0002667611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3444605,"threshold_uncertainty_score":0.9998367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2979085823781145,"score_gpt":0.4758946121106599,"score_spread":0.1779860297325455,"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."}}