{"id":"W2801638768","doi":"10.1515/hf-2017-0213","title":"Optical characteristics of Douglas fir at various densities, grain directions and thicknesses investigated by near-infrared spatially resolved spectroscopy (NIR-SRS)","year":2018,"lang":"en","type":"article","venue":"Holzforschung","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations; University of British Columbia","funders":"","keywords":"Spectroscopy; Analytical Chemistry (journal); Materials science; Scattering; Near-infrared spectroscopy; Hyperspectral imaging; Absorption (acoustics); Optics; Chemistry; Physics; Remote sensing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001039729,0.0002463293,0.0003250314,0.00005887188,0.0002461048,0.00008727988,0.00009769618,0.000146728,0.00008928875],"category_scores_gemma":[0.00009213293,0.0002245235,0.00004639737,0.0001746008,0.0004091298,0.0001484026,0.00007132017,0.0001621123,0.00003307646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007561417,"about_ca_system_score_gemma":0.00004472584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002167885,"about_ca_topic_score_gemma":0.0002594905,"domain_scores_codex":[0.9989465,0.00003590173,0.0003180696,0.0002129751,0.0001630171,0.0003235662],"domain_scores_gemma":[0.999382,0.00008905407,0.0000585631,0.0002503883,0.00008547211,0.0001345559],"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":[0.000804897,0.0003185706,0.09593693,0.0008772639,0.001301096,0.0001090706,0.01158288,0.0001039497,0.8133839,0.001345816,0.06716821,0.007067361],"study_design_scores_gemma":[0.002444695,0.001297521,0.1195384,0.0004104643,0.0004458369,0.000107821,0.0001963321,0.0221073,0.7701527,0.0008904731,0.08103152,0.001376934],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935527,0.00129302,0.0003650394,0.00009741929,0.0006555854,0.0002067894,0.00008880623,0.00032713,0.003413515],"genre_scores_gemma":[0.9936404,0.000386141,0.004388824,0.0000497799,0.0002328543,0.00002173109,0.0001231024,0.00005571326,0.001101495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04323126,"threshold_uncertainty_score":0.9155803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008405632244253978,"score_gpt":0.1978495832665155,"score_spread":0.1894439510222615,"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."}}