{"id":"W36398867","doi":"10.1007/s00107-010-0490-2","title":"Wet-pocket classification in Abies lasiocarpa using spectroscopy in the visible and near infrared range","year":2010,"lang":"en","type":"article","venue":"European Journal of Wood and Wood Products","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Near-infrared spectroscopy; Moisture; Linear discriminant analysis; Spectroscopy; Abies lasiocarpa; Water content; Analytical Chemistry (journal); Materials science; Mathematics; Chemistry; Botany; Composite material; Chromatography; Optics; Physics; Pinus contorta; Statistics; Geology","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":[0.001010858,0.0001528577,0.0002499291,0.0002098166,0.0001039324,0.0001701367,0.0002441283,0.00003944959,0.0000937975],"category_scores_gemma":[0.0003626716,0.0001092467,0.00003470065,0.0005870537,0.0001268609,0.0002275854,0.00004323645,0.0006742033,0.0000027728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001892336,"about_ca_system_score_gemma":0.00006240165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007814187,"about_ca_topic_score_gemma":0.000006292637,"domain_scores_codex":[0.9988281,0.0001239283,0.000412581,0.000219046,0.0002041747,0.0002122341],"domain_scores_gemma":[0.9992765,0.00007037732,0.0002690056,0.0002436685,0.00007683982,0.00006365265],"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":[0.0001190655,0.0002043136,0.02623691,0.000110463,0.00004570956,0.0001458107,0.002874953,0.000004600637,0.9680528,0.0001007552,0.0007339187,0.001370715],"study_design_scores_gemma":[0.005345489,0.0005357625,0.2012261,0.000316834,0.0003536069,0.001445206,0.007705006,0.00026784,0.7664064,0.001115964,0.01450325,0.000778582],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884185,0.002814326,0.000007737835,0.001020437,0.00008352139,0.00005018147,0.000002619168,0.000007649455,0.007595005],"genre_scores_gemma":[0.9969008,0.0003298924,0.002105757,0.000122202,0.0004132293,5.258941e-7,0.000001719812,0.00001994846,0.0001059442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2016464,"threshold_uncertainty_score":0.4454949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02564503330642192,"score_gpt":0.266738146524905,"score_spread":0.2410931132184831,"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."}}