{"id":"W2365548575","doi":"","title":"Results Analysis on Microbial Detection of Drinking Water in Shenyang Railway Area","year":2011,"lang":"en","type":"article","venue":"Zhiye yu jiankang","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Water supply; Significant difference; Quarter (Canadian coin); Water quality; Water source; Coliform bacteria; Pollution; Environmental engineering; Water pressure; Water safety; Toxicology; Water resource management; Medicine; Bacteria; Geography; Biology; Ecology","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":[0.0001774884,0.0002840753,0.0001633326,0.0007359872,0.0003662512,0.0002315983,0.0001072945,0.0002270094,0.001431642],"category_scores_gemma":[0.0002698033,0.00008999382,0.0002691697,0.0006334006,0.0001608403,0.0001746777,0.0002198045,0.00008798109,0.0001611117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000131339,"about_ca_system_score_gemma":0.0002029101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004535042,"about_ca_topic_score_gemma":0.005478295,"domain_scores_codex":[0.9997584,0.00002829808,0.00002625396,0.00006494435,0.0000836624,0.0000385004],"domain_scores_gemma":[0.9998376,0.00002716447,0.00004009731,0.000006020224,0.00006386194,0.00002516871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003420224,0.0001406352,0.6915454,0.000247632,0.00005298996,0.000530417,0.001074301,0.0003018175,0.2858855,0.00006613159,0.0003558173,0.01945733],"study_design_scores_gemma":[0.000006253933,0.0002510987,0.973112,0.000007703187,0.00003780052,0.0001980568,0.0007889049,0.0004865722,0.02430984,0.00002643239,0.000767988,0.00000736092],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985383,0.00006168075,0.000370106,0.0000222195,0.000003026611,0.00001001167,0.0003513007,0.000008694809,0.0006348392],"genre_scores_gemma":[0.9978952,0.00007086893,0.0006423845,0.00001731677,0.000003725923,0.00001974176,0.0007085164,0.000001903475,0.0006403885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004535042,"threshold_uncertainty_score":0.009017289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03488939788555592,"score_gpt":0.2267695775626858,"score_spread":0.1918801796771299,"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."}}