{"id":"W3015285002","doi":"10.3390/molecules25071719","title":"Green Approaches to Sample Preparation Based on Extraction Techniques","year":2020,"lang":"en","type":"review","venue":"Molecules","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":116,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sample preparation; Sample (material); Environmentally friendly; Bioanalysis; Hazardous waste; Process engineering; Computer science; Biochemical engineering; Extraction (chemistry); Process (computing); Nanotechnology; Chemistry; Chromatography; Engineering; Materials science; Waste management","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":[0.0008912813,0.001477447,0.001207557,0.002656454,0.0004534251,0.00113797,0.0009898088,0.00127806,0.003740289],"category_scores_gemma":[0.0005965437,0.0005831028,0.0007970625,0.001846023,0.0008830816,0.001810882,0.001072805,0.002521043,0.003896094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006294736,"about_ca_system_score_gemma":0.0006835665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003879851,"about_ca_topic_score_gemma":0.0006691036,"domain_scores_codex":[0.9991224,0.0001147052,0.00004726023,0.0001839533,0.0004660145,0.00006556085],"domain_scores_gemma":[0.9997014,0.0001329254,0.00004601466,0.00002230841,0.00008212048,0.00001517939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001106433,0.0002672761,0.0002866002,0.02381902,0.0001434009,0.0006269998,0.0002373747,0.00153208,0.2043681,0.03853926,0.01949236,0.7105768],"study_design_scores_gemma":[0.00001069076,0.0002305669,0.00045308,0.0009456237,0.00007023992,0.001423494,0.00006842279,0.0006723829,0.1113934,0.007246391,0.8774258,0.00005974753],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004666185,0.9021386,0.06499206,0.0009653593,0.001429832,0.0003305876,0.0002935813,0.0003143311,0.02486951],"genre_scores_gemma":[0.01743682,0.9336604,0.03367112,0.001095993,0.0006627247,0.0002970734,0.000385304,0.00005794,0.01273267],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003740289,"threshold_uncertainty_score":0.01251251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1982455443029129,"score_gpt":0.380781931222443,"score_spread":0.1825363869195301,"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."}}