{"id":"W2113565971","doi":"10.3390/ijerph120403600","title":"Integrating Environmental and Human Health Databases in the Great Lakes Basin: Themes, Challenges and Future Directions","year":2015,"lang":"en","type":"review","venue":"International Journal of Environmental Research and Public Health","topic":"Environmental Justice and Health Disparities","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Public Health Ontario; University of Toronto; Toronto Public Health","funders":"","keywords":"Harmonization; Environmental data; Stakeholder; Government (linguistics); Business; Environmental resource management; Resource (disambiguation); Environmental health; Environmental planning; Data science; Database; Geography; Computer science; Medicine; Political science; Public relations","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007555554,0.0002450889,0.0007137216,0.0004823463,0.0009146301,0.0002362749,0.000498024,0.0001090367,0.0001164129],"category_scores_gemma":[0.0001150674,0.0001725842,0.00007637162,0.00008788982,0.00116697,0.0005911122,0.0002626051,0.001225798,0.000004046695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001244369,"about_ca_system_score_gemma":0.0007610829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001286532,"about_ca_topic_score_gemma":0.005748468,"domain_scores_codex":[0.9943091,0.002315958,0.0008089148,0.0003351822,0.001585824,0.0006450478],"domain_scores_gemma":[0.9978803,0.0007386697,0.0005119811,0.0001552696,0.00001870042,0.0006951171],"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":[0.000007441819,0.0003335201,0.0007004621,0.0008359899,0.00005132883,0.00002221102,0.01331451,5.463059e-9,9.025369e-8,0.006855982,0.0005664301,0.977312],"study_design_scores_gemma":[0.0002289653,0.0003221227,0.004444083,0.001335979,0.0000108344,0.0001686677,0.09402679,1.945183e-7,8.76894e-9,0.0002561523,0.8990983,0.0001079215],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001808954,0.9722094,7.876296e-7,0.02420325,0.0001986341,0.0005171734,0.0003014767,0.000004402181,0.000755941],"genre_scores_gemma":[0.003738469,0.9941722,0.00008287569,0.0005564056,0.001182137,0.00002961564,0.0001140449,0.00002095089,0.0001033297],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9772041,"threshold_uncertainty_score":0.7037779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2719227855364693,"score_gpt":0.4869351758399808,"score_spread":0.2150123903035115,"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."}}