{"id":"W2948953144","doi":"10.1016/j.sab.2019.05.018","title":"A simple and efficient centrifugation filtration method for bacterial concentration and isolation prior to testing liquid specimens with laser-induced breakdown spectroscopy","year":2019,"lang":"en","type":"article","venue":"Spectrochimica Acta Part B Atomic Spectroscopy","topic":"Laser-induced spectroscopy and plasma","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Universities Space Research Association; University of Windsor; Natural Sciences and Engineering Research Council of Canada; Research Triangle Institute","keywords":"Filtration (mathematics); Suspension (topology); Centrifugation; Materials science; Filter (signal processing); Chromatography; Contamination; Analytical Chemistry (journal); Filter paper; Insert (composites); Chemistry; Composite material; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004904975,0.001355824,0.001059533,0.001583467,0.0008575812,0.0007037501,0.001006645,0.000838712,0.001829004],"category_scores_gemma":[0.0007612159,0.0005243121,0.0007342911,0.0005746388,0.0003780732,0.0007484187,0.0008239917,0.001263481,0.003317191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002878324,"about_ca_system_score_gemma":0.0008059255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006654058,"about_ca_topic_score_gemma":0.001581262,"domain_scores_codex":[0.998985,0.00009901298,0.0001035954,0.0001711862,0.0005578504,0.00008338063],"domain_scores_gemma":[0.9994937,0.0001010017,0.00008963692,0.00009903487,0.0001616621,0.00005498198],"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":[0.00002083605,0.00008385198,0.0002274216,0.00008153717,0.000009277404,0.00005522572,0.00001578697,0.00003559012,0.9867789,0.0001414739,0.0005232781,0.0120269],"study_design_scores_gemma":[0.0000177352,0.0003039206,0.004716877,0.00003015269,0.00005810503,0.001027739,0.00003954265,0.001654693,0.9768831,0.0002495162,0.01495637,0.0000623348],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1451361,0.007637542,0.8291309,0.000965555,0.00111405,0.001716117,0.001834091,0.005470419,0.00699534],"genre_scores_gemma":[0.3005616,0.004159354,0.6781077,0.0006551318,0.0003258146,0.001472576,0.003727995,0.0005053183,0.01048444],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001829004,"threshold_uncertainty_score":0.006118596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00963957648108292,"score_gpt":0.2415726123263356,"score_spread":0.2319330358452527,"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."}}