{"id":"W2999050896","doi":"10.1002/app.48951","title":"Preparation and properties of novel corn straw cellulose–based superabsorbent with water‐retaining and slow‐release functions","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Polymer Science","topic":"Polymer-Based Agricultural Enhancements","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Superabsorbent polymer; Cellulose; Distilled water; Thermogravimetric analysis; Nuclear chemistry; Straw; Fourier transform infrared spectroscopy; Chemistry; Materials science; Leaching (pedology); Aqueous solution; Polymer; Polymer chemistry; Chemical engineering; Organic chemistry; Soil water; Chromatography; Inorganic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001201619,0.0001268336,0.0001737196,0.00007752005,0.00009021695,0.00006154718,0.0001249934,0.0000245821,0.00000796007],"category_scores_gemma":[0.000003302842,0.00007243732,0.00001912269,0.0002303533,0.0002204457,0.0003464544,0.00002572164,0.0001228553,0.000001028943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002652509,"about_ca_system_score_gemma":0.00007276695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006375001,"about_ca_topic_score_gemma":0.000001452989,"domain_scores_codex":[0.9990243,0.000004444119,0.0002807305,0.0001422028,0.0003534833,0.0001948278],"domain_scores_gemma":[0.9995779,0.00001061351,0.00008751881,0.00006487485,0.00007010889,0.0001889415],"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":[0.0001277169,0.00002592194,0.00006181953,0.00004796206,0.00001574595,0.000001174905,0.001147849,0.003425776,0.9941939,0.00003701469,0.00001111446,0.0009039713],"study_design_scores_gemma":[0.0006692418,0.0002636548,0.0002045145,0.0000535102,0.00003257754,0.00001098215,0.0003341608,0.02421976,0.974081,7.929838e-7,0.00001880464,0.0001110147],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963813,0.0004811858,0.002540438,0.0001555563,0.00005381737,0.0001073359,0.000003695752,0.00002102292,0.0002556866],"genre_scores_gemma":[0.9994648,0.000008641524,0.0003877097,0.00007380476,0.00003926526,0.000004068158,9.971241e-7,0.000007825912,0.00001294072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02079399,"threshold_uncertainty_score":0.2953908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014597257476932,"score_gpt":0.1952504917483444,"score_spread":0.1806532342714124,"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."}}