{"id":"W2972823914","doi":"10.4095/315138","title":"Evaluation of single-use nylon-screened sieves for use with fine-grained sediment samples","year":2019,"lang":"en","type":"report","venue":"","topic":"Polymer-Based Agricultural Enhancements","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Sieve (category theory); Sieve analysis; Molecular sieve; Fraction (chemistry); Materials science; Mineralogy; Contamination; Reuse; Pulp and paper industry; Environmental science; Chemistry; Waste management; Chromatography; Mathematics; Nanotechnology; Engineering; Biology; Adsorption; Organic chemistry","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":[0.001267115,0.0004753896,0.0003210399,0.0008007681,0.0005112767,0.0007291721,0.0005637589,0.0004658843,0.000952301],"category_scores_gemma":[0.002277112,0.0002124862,0.0003380547,0.0004799466,0.0002607571,0.0004201671,0.000322289,0.0002433769,0.0003619044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002370352,"about_ca_system_score_gemma":0.0004418616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001320349,"about_ca_topic_score_gemma":0.006346525,"domain_scores_codex":[0.9986929,0.0002102977,0.0001269018,0.0001740863,0.0007262205,0.00006955687],"domain_scores_gemma":[0.9983366,0.0004887469,0.0003302316,0.0001312196,0.0006362018,0.0000769076],"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":[0.0002913878,0.0002999304,0.01155388,0.0002773334,0.00005054515,0.0001513245,0.000307375,0.0004354213,0.940594,0.00007723866,0.00008910477,0.04587236],"study_design_scores_gemma":[0.000008507285,0.001900528,0.0232024,0.00003445185,0.00006045093,0.0003463935,0.0002707226,0.0006987643,0.9705908,0.00003302539,0.002838201,0.00001577259],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978296,0.000859189,0.01785172,0.00004541461,0.0000357149,0.0003825419,0.0002890228,0.0001444515,0.002095978],"genre_scores_gemma":[0.8600662,0.002192859,0.1306551,0.00007300985,0.0000172383,0.0002563335,0.0008127766,0.000123783,0.005802626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001320349,"threshold_uncertainty_score":0.006701231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1259843486435206,"score_gpt":0.2887364003229485,"score_spread":0.1627520516794279,"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."}}