{"id":"W2800389476","doi":"10.1117/12.2303976","title":"Influence of surface roughness, volume diffusion and particle size in reflectance infrared spectroscopy","year":2018,"lang":"en","type":"article","venue":"","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Materials science; Surface roughness; Spectroscopy; Volume (thermodynamics); Optics; Diffusion; Infrared spectroscopy; Surface finish; Reflectivity; Infrared; Particle (ecology); Diffuse reflectance infrared fourier transform; Diffuse reflection; Surface (topology); Chemistry; Composite material; Physics; Geology; Geometry; Thermodynamics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001080698,0.0003707192,0.000402444,0.0004732314,0.0002348228,0.0005174115,0.0003554818,0.0004407834,0.0004399543],"category_scores_gemma":[0.001960166,0.0002434526,0.0004530559,0.0002564635,0.000407218,0.0006060443,0.0002683907,0.0004250059,0.0001796083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003235441,"about_ca_system_score_gemma":0.0001258189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002271873,"about_ca_topic_score_gemma":0.003175293,"domain_scores_codex":[0.9990743,0.0001809481,0.00004913365,0.0001417987,0.0004720028,0.00008165879],"domain_scores_gemma":[0.9976898,0.001594502,0.0002224607,0.0001312288,0.0003172121,0.0000448304],"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":[0.0002402689,0.00004668489,0.003348137,0.0001510165,0.00003656589,0.0001371466,0.000101599,0.002015866,0.9777575,0.0001929107,0.0001275682,0.01584471],"study_design_scores_gemma":[0.000008203246,0.0003428554,0.01572483,0.00001128177,0.00004905775,0.0002060592,0.0001449317,0.0123624,0.9696731,0.0001826548,0.001257291,0.00003733313],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9587147,0.005572658,0.03138837,0.0001545469,0.000114162,0.00008660958,0.0001744452,0.0002495126,0.003544982],"genre_scores_gemma":[0.9883254,0.001405119,0.009125685,0.0000522889,0.00001676897,0.00001899297,0.0001134236,0.00004818785,0.0008942067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002271873,"threshold_uncertainty_score":0.005715311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009437113282039031,"score_gpt":0.2569073378355115,"score_spread":0.2474702245534725,"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."}}