{"id":"W4315475369","doi":"10.1016/j.jobab.2023.01.004","title":"In-situ polymerization of lignocelluloses of autohydrolysis process with acrylamide","year":2023,"lang":"en","type":"article","venue":"Journal of Bioresources and Bioproducts","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; Northern Ontario Heritage Fund Corporation","keywords":"Acrylamide; Polymerization; Chemistry; Gel permeation chromatography; Flocculation; Molar mass; Chromatography; Raw material; Hydrolysate; Zeta potential; Polymer; Permeation; Nuclear chemistry; Polymer chemistry; Chemical engineering; Organic chemistry; Hydrolysis; Monomer; Membrane","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0001540553,0.0004494701,0.0001942598,0.0001380608,0.00007295167,0.0001616853,0.0001427578,0.0001759986,0.0005841127],"category_scores_gemma":[0.0001103134,0.0001329025,0.0002946384,0.0001249592,0.0001135256,0.0002646339,0.0001428536,0.0004387784,0.0001636063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001196481,"about_ca_system_score_gemma":0.0001536708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003142051,"about_ca_topic_score_gemma":0.0007470581,"domain_scores_codex":[0.9999081,0.00001581831,0.00000570747,0.00002029403,0.00002513791,0.00002495342],"domain_scores_gemma":[0.9999281,0.00001244515,0.00002955485,0.000008019027,0.00001108238,0.00001071451],"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":[0.000008788503,0.000007058461,0.00002885159,0.00003557168,0.00000346944,0.00001790345,0.000007116766,0.00004233046,0.999181,0.00002006937,0.000003487094,0.0006443943],"study_design_scores_gemma":[0.000001229925,0.00004797317,0.00031764,0.000001827273,0.000005245761,0.00003530175,0.000004223969,0.0002207448,0.9989472,0.000007562668,0.0004098046,0.000001305662],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800184,0.002818528,0.01541503,0.00005121711,0.0000326863,0.00003597366,0.00006090477,0.00005265066,0.001514501],"genre_scores_gemma":[0.9897057,0.001432922,0.006785126,0.00003481005,0.00001310346,0.00001564085,0.00006875013,0.00001541708,0.001928437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005841127,"threshold_uncertainty_score":0.001954079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01117379851102408,"score_gpt":0.2644526565195106,"score_spread":0.2532788580084865,"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."}}