{"id":"W3197854849","doi":"10.3390/polym13172884","title":"Innovative Polyelectrolyte Treatment to Flame-Retard Wood","year":2021,"lang":"en","type":"article","venue":"Polymers","topic":"Flame retardant materials and properties","field":"Materials Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Natural Sciences and Engineering Research Council of Canada","funders":"Division of Materials Research; Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Polyelectrolyte; Environmentally friendly; Materials science; Coating; Fire retardant; Composite material; Engineered wood; Pulp and paper industry; Sodium salt; Waste management; Environmental science; Chemistry; Polymer; 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":[0.000100998,0.0003936812,0.0001499974,0.0001898052,0.00009826212,0.0001971151,0.000177569,0.000339561,0.0007949554],"category_scores_gemma":[0.00007446102,0.0001113335,0.000236608,0.0001324368,0.0001224238,0.0002831293,0.0001449409,0.0004612373,0.0002662831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009796367,"about_ca_system_score_gemma":0.0001074323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001759978,"about_ca_topic_score_gemma":0.0005677747,"domain_scores_codex":[0.9999233,0.000008528446,0.000003980897,0.00001832829,0.00002724565,0.0000185616],"domain_scores_gemma":[0.9999764,0.000003348611,0.000006923855,0.000002543683,0.000005754564,0.000005032809],"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":[0.00001500056,0.00001746929,0.00003149163,0.00006131383,0.000003565596,0.0000303924,0.00000709692,0.00007949315,0.9965886,0.0001051747,0.00003232624,0.003028148],"study_design_scores_gemma":[0.000004191357,0.0001419456,0.000376582,0.000003792561,0.000006745707,0.000082504,0.000007027595,0.0005919824,0.9958302,0.00003522756,0.002916015,0.000003741101],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358832,0.007426037,0.04979326,0.0001728065,0.0002275383,0.0001428783,0.0001638007,0.0002461398,0.005944445],"genre_scores_gemma":[0.9762004,0.002721731,0.01575645,0.0001119661,0.00002303985,0.00005081305,0.0001448222,0.00002931454,0.004961458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007949554,"threshold_uncertainty_score":0.00265938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01772674421089348,"score_gpt":0.2441686942011458,"score_spread":0.2264419499902523,"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."}}