{"id":"W4413890221","doi":"10.1016/j.jece.2025.119038","title":"Short-wave infrared hyperspectral imaging of microplastics: Effects of chemical and physical processes on spectral signatures and detection capabilities","year":2025,"lang":"en","type":"article","venue":"Journal of environmental chemical engineering","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Environment and Climate Change Canada","keywords":"Microplastics; Hyperspectral imaging; Chemical imaging; Infrared; Spectral signature; Remote sensing; Environmental science; Environmental chemistry; Chemistry; Optics; Geology; Physics","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":[0.00101591,0.0006070136,0.000332016,0.0003719227,0.0001421083,0.0004454674,0.0003755803,0.0005398158,0.0008247669],"category_scores_gemma":[0.001122111,0.0003587164,0.0002941587,0.0002436446,0.0005107239,0.0008088116,0.0003238005,0.0005435751,0.0003640713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001464852,"about_ca_system_score_gemma":0.0001274403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000264583,"about_ca_topic_score_gemma":0.0006171447,"domain_scores_codex":[0.9995081,0.0001245952,0.00002464814,0.00009925244,0.0002008968,0.00004247406],"domain_scores_gemma":[0.9991651,0.0004292828,0.0001540667,0.00005628031,0.0001456453,0.00004967336],"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":[0.00007713338,0.00001768665,0.0004877658,0.00007193092,0.00001018274,0.00001970197,0.00002421845,0.0002423521,0.9932889,0.00003102855,0.00002289183,0.005706312],"study_design_scores_gemma":[0.0000033903,0.0002585751,0.006271952,0.00000684721,0.00002556231,0.0002203098,0.00003831602,0.007344597,0.9851511,0.00004874526,0.0006145312,0.00001600091],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9293591,0.002402903,0.06550538,0.000124618,0.00004082362,0.0000542112,0.0001040792,0.0004374278,0.001971434],"genre_scores_gemma":[0.8832224,0.002078377,0.1116163,0.0001903956,0.00003797141,0.00008195655,0.0002271741,0.0001288925,0.002416435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00101591,"threshold_uncertainty_score":0.005372763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001783539184831432,"score_gpt":0.1606907521919227,"score_spread":0.1589072130070913,"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."}}