{"id":"W4210853837","doi":"10.1021/acs.analchem.1c04569","title":"Targeted Analysis of Microplastics Using Discrete Frequency Infrared Imaging","year":2022,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dow Chemical (Canada)","funders":"","keywords":"Microplastics; Infrared; Sample (material); Quantum cascade laser; Chemistry; Chemical imaging; Throughput; Sample preparation; Laser; Wavelength; Nanotechnology; Biological system; Optoelectronics; Analytical Chemistry (journal); Optics; Process engineering; Cascade; Hyperspectral imaging; Chromatography; Environmental chemistry; Artificial intelligence; Materials science; Computer science; Telecommunications; Physics","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":[0.0006386494,0.0006022499,0.0003657893,0.0008384243,0.0002261828,0.0005522154,0.0006838751,0.0006153918,0.0006673317],"category_scores_gemma":[0.0006199486,0.0003637057,0.000432162,0.0003231477,0.0005476928,0.0008612219,0.0006036838,0.0007328441,0.0004150562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000475953,"about_ca_system_score_gemma":0.0003979526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004660975,"about_ca_topic_score_gemma":0.0009582361,"domain_scores_codex":[0.999482,0.00004595659,0.00002114522,0.0001470494,0.0002518942,0.0000521119],"domain_scores_gemma":[0.9995229,0.0001580492,0.000102762,0.00005424405,0.0001299344,0.00003218961],"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":[0.00001900499,0.00001545357,0.00013321,0.00003753371,0.000003860855,0.00002385028,0.00001646458,0.0001929521,0.9945452,0.0001712445,0.00004274557,0.004798466],"study_design_scores_gemma":[0.000003817869,0.0000935692,0.0003805201,0.000003494067,0.000007199335,0.00007756826,0.000009896652,0.005713999,0.9928138,0.00007022366,0.0008159211,0.00001005408],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4329942,0.001222705,0.5610691,0.0002183551,0.00009304736,0.0002949477,0.0002540897,0.001476257,0.002377237],"genre_scores_gemma":[0.6070176,0.001007788,0.3876686,0.0002052897,0.00003604346,0.0002822127,0.0002151063,0.00009651151,0.003470749],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008384243,"threshold_uncertainty_score":0.003453314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007340065597510555,"score_gpt":0.2214275390490348,"score_spread":0.2140874734515243,"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."}}