{"id":"W2589442859","doi":"10.1515/hf-2016-0145","title":"Characterizing spatial distribution of the adsorbed water in wood cell wall of <i>Ginkgo biloba</i> L. by μ-FTIR and confocal Raman spectroscopy","year":2017,"lang":"en","type":"article","venue":"Holzforschung","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Fourier transform infrared spectroscopy; Confocal; Raman spectroscopy; Adsorption; Analytical Chemistry (journal); Spectroscopy; Chemistry; Infrared spectroscopy; Materials science; Chemical engineering; Chromatography; Optics; 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":[0.00007087854,0.0002225038,0.0001143535,0.0002312622,0.0001276233,0.0001681574,0.0001270138,0.0001510022,0.0006638014],"category_scores_gemma":[0.00007982815,0.0001145076,0.000137417,0.0001209235,0.0001676468,0.0002106413,0.0001255549,0.000239595,0.0001282842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008836231,"about_ca_system_score_gemma":0.00005934935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008417499,"about_ca_topic_score_gemma":0.0008889333,"domain_scores_codex":[0.999965,0.000004158608,0.000001528192,0.00001166353,0.000008448068,0.00000915177],"domain_scores_gemma":[0.9999456,0.0000127065,0.0000163118,0.000003741221,0.00001241524,0.000009224513],"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":[0.00001994849,0.000002525176,0.0001382122,0.000008796329,0.000001019251,0.000006372639,0.000008487801,0.00001273709,0.9995541,0.000007795116,0.000003319068,0.0002366076],"study_design_scores_gemma":[0.000002959221,0.00005604067,0.01430522,0.000003001213,0.00001105451,0.00005356074,0.00007367489,0.001067719,0.984101,0.0000286459,0.0002907459,0.000006374537],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977707,0.0002167117,0.001549976,0.00001610933,0.000003876132,0.00000374803,0.00008235262,0.00001949403,0.0003369837],"genre_scores_gemma":[0.9976445,0.000139957,0.001376944,0.00001877434,0.00000207338,0.00001075026,0.0001581423,0.00001667364,0.0006322826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008417499,"threshold_uncertainty_score":0.002220571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005786402932828164,"score_gpt":0.1841249948000574,"score_spread":0.1783385918672293,"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."}}