{"id":"W1023745804","doi":"10.1080/11287462.2011.10800700","title":"Assessing and Monitoring Microbiological Quality of Surface Waters Using Tele-Epidemiology","year":2011,"lang":"en","type":"article","venue":"Global Bioethics","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Public Health Agency of Canada","funders":"","keywords":"Geospatial analysis; Public health; Epidemiology; Environmental health; Water quality; Environmental planning; Waterborne diseases; Geomatics; Environmental epidemiology; Surface water; Environmental resource management; Risk assessment; Agriculture; Environmental science; Geography; Environmental engineering; Remote sensing; Ecology; Medicine; Biology; Computer science","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":[0.000882249,0.0004366389,0.0004786993,0.002197067,0.0002477003,0.0009564497,0.0004614147,0.000678775,0.00112988],"category_scores_gemma":[0.001481534,0.0001952978,0.0004007683,0.002338026,0.0003268378,0.001118421,0.0006898176,0.0003775821,0.0004560531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003749918,"about_ca_system_score_gemma":0.0004209779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00242802,"about_ca_topic_score_gemma":0.003806439,"domain_scores_codex":[0.9988127,0.0004031888,0.00008693223,0.0002312452,0.0004044014,0.00006159282],"domain_scores_gemma":[0.9979489,0.0004395032,0.0008270828,0.0001722942,0.0005315664,0.00008067527],"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":[0.0002542116,0.0003744569,0.6571279,0.0006953283,0.0001646109,0.0001500985,0.0004103855,0.003406473,0.0749559,0.0005948053,0.001103962,0.2607619],"study_design_scores_gemma":[0.00004113874,0.001956006,0.8443409,0.0004041245,0.0004621054,0.00166091,0.002005351,0.0301736,0.0962311,0.002955327,0.01964056,0.0001288907],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8454892,0.007658876,0.1218403,0.0009291187,0.0001667349,0.0006057271,0.006418649,0.0006898713,0.01620151],"genre_scores_gemma":[0.9081886,0.005158902,0.08045459,0.0003063999,0.00009821675,0.0003172593,0.002063297,0.00002810889,0.003384641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00242802,"threshold_uncertainty_score":0.004827738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5401395705368643,"score_gpt":0.4539994945511288,"score_spread":0.08614007598573553,"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."}}