{"id":"W3005419361","doi":"10.1002/cjce.23721","title":"New insight about the relationship between the main characteristics of precursor materials and activated carbon properties using multivariate analysis","year":2020,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Natural Fiber Reinforced Composites","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lignin; Cellulose; Carbon fibers; Activated carbon; Materials science; Multivariate statistics; Chemical engineering; Characterization (materials science); Volume (thermodynamics); Principal component analysis; Organic chemistry; Chemistry; Composite material; Nanotechnology; Mathematics; Adsorption; Composite number","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004757164,0.0005935189,0.0002923587,0.001162274,0.0001396865,0.0007777105,0.0001592112,0.0002374045,0.001067214],"category_scores_gemma":[0.00128114,0.0001967532,0.0003993235,0.0009691484,0.0004057505,0.0005783346,0.0001911391,0.0005790388,0.0001425786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002174745,"about_ca_system_score_gemma":0.000339203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001043676,"about_ca_topic_score_gemma":0.0009762946,"domain_scores_codex":[0.9998102,0.00005520427,0.000009457865,0.00004743179,0.00005670938,0.00002104572],"domain_scores_gemma":[0.9991554,0.0004928153,0.0001323392,0.00006785736,0.0001159239,0.00003568548],"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":[0.0004583353,0.0007006616,0.09646971,0.0006236379,0.0004182545,0.0005396452,0.0003168985,0.05551214,0.6343867,0.01021407,0.001032067,0.1993278],"study_design_scores_gemma":[0.00002036243,0.0003892211,0.1954788,0.00004591083,0.0002362257,0.000602804,0.0002406337,0.6458839,0.1397438,0.01357186,0.003651423,0.0001350252],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.791546,0.001095287,0.203027,0.0001959794,0.00002702235,0.00003733514,0.0006415886,0.0003323658,0.003097354],"genre_scores_gemma":[0.9799666,0.0003275814,0.01908175,0.00001387411,0.00001675145,0.00001168233,0.000176058,0.00001947022,0.0003862245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001162274,"threshold_uncertainty_score":0.003570199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.032569804767062,"score_gpt":0.2225359504740938,"score_spread":0.1899661457070318,"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."}}