{"id":"W2086981411","doi":"10.1007/s00226-006-0116-3","title":"A NMR study of water distribution in hardwoods at several equilibrium moisture contents","year":2006,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Wood Treatment and Properties","field":"Engineering","cited_by":130,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Bound water; Equilibrium moisture content; Robinia; Softwood; Moisture; Water content; Desorption; Chemistry; Liquid water; Free water; Hardwood; Analytical Chemistry (journal); Materials science; Sorption; Composite material; Botany; Chromatography; Thermodynamics; Organic chemistry; Environmental science; Physics; Adsorption; Environmental engineering","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":[0.0001559312,0.0002058664,0.0001613438,0.0002094008,0.0004685498,0.0002135727,0.0003041038,0.0002740854,0.002561849],"category_scores_gemma":[0.000243353,0.0001659761,0.0001395932,0.0001908104,0.0004044048,0.000606571,0.0001791267,0.0005085982,0.0002099261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001709095,"about_ca_system_score_gemma":0.0001319929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001004842,"about_ca_topic_score_gemma":0.001114906,"domain_scores_codex":[0.9999363,0.000008923516,0.000001692449,0.00001747506,0.00001363308,0.00002196908],"domain_scores_gemma":[0.9998061,0.00008459468,0.00002321175,0.00001577794,0.00003830278,0.00003199347],"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":[0.0003203939,0.00004047874,0.000347746,0.00003856733,0.000005472453,0.00005226796,0.00004288324,0.0001570278,0.9973068,0.0001152885,0.0000571381,0.001515968],"study_design_scores_gemma":[0.00005316946,0.0007820266,0.01150208,0.00001088604,0.00003591678,0.000237221,0.0001383297,0.003318995,0.9821506,0.0002532539,0.00149719,0.00002031655],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924067,0.0006225213,0.003781641,0.00008554646,0.00001674063,0.00001532135,0.0001709927,0.00005166786,0.002848912],"genre_scores_gemma":[0.9967331,0.0002691995,0.001404667,0.00005230599,0.0000206386,0.00001509905,0.0001785018,0.00001276271,0.001313807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002561849,"threshold_uncertainty_score":0.008570194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008009675483183395,"score_gpt":0.1964882536794592,"score_spread":0.1884785781962758,"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."}}