{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000583031,0.0001171173,0.0001851911,0.0001672809,0.00008089611,0.00001115934,0.0001479389,0.00007866632,0.000256315],"category_scores_gemma":[0.00005815953,0.00009528002,0.0001050314,0.0004327157,0.00007156163,0.000117258,0.00009772656,0.000144567,0.0001135412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001248907,"about_ca_system_score_gemma":0.000001844504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002136637,"about_ca_topic_score_gemma":0.0009354786,"domain_scores_codex":[0.9988094,0.00007395927,0.0003413022,0.0003023022,0.0001917753,0.0002812719],"domain_scores_gemma":[0.9995371,0.00003876839,0.0001247839,0.0002463729,0.000006149338,0.00004684577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005062707,0.0003342375,0.3227227,0.00002315044,0.0001673084,0.00003948276,0.03709728,0.007452118,0.5825445,0.00001893135,0.00006403805,0.04902991],"study_design_scores_gemma":[0.000518411,0.0001319096,0.3887614,0.00005799275,0.000083126,0.000002280421,0.0004148569,0.001830999,0.6073911,0.0001010808,0.0004550959,0.0002517281],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986757,0.000003400499,0.0004150053,0.00002305534,0.0001420899,0.00007343935,0.000003276687,0.00003133491,0.01255134],"genre_scores_gemma":[0.9988925,0.000001460171,0.0007204615,0.00002146157,0.00004855333,0.000004549675,0.00000683399,0.000009627531,0.00029454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06603868,"threshold_uncertainty_score":0.3885406,"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."}}