{"id":"W2051636438","doi":"10.1016/j.foodhyd.2014.09.031","title":"Non-starch polysaccharides from American ginseng: physicochemical investigation and structural characterization","year":2014,"lang":"en","type":"article","venue":"Food Hydrocolloids","topic":"Polysaccharides and Plant Cell Walls","field":"Agricultural and Biological Sciences","cited_by":104,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Chemistry; Rhamnose; Polysaccharide; Arabinose; Fourier transform infrared spectroscopy; Pectin; Starch; Xylose; Uronic acid; Residue (chemistry); Intrinsic viscosity; Chemical structure; Galactose; Monosaccharide; Sugar; Nuclear magnetic resonance spectroscopy; Chromatography; Organic chemistry; Biochemistry; Fermentation; Polymer; Chemical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000867548,0.0001843487,0.0002346798,0.00001593763,0.0001808213,0.000110786,0.0001738386,0.0000746901,0.00007531615],"category_scores_gemma":[0.00002020869,0.00008629128,0.00005383015,0.0002510207,0.0001126011,0.0001797501,0.00006761568,0.0001308045,0.00001705945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001681221,"about_ca_system_score_gemma":0.000006813085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001100563,"about_ca_topic_score_gemma":0.0002959582,"domain_scores_codex":[0.9989333,0.0000452821,0.0001980929,0.0003619599,0.0001893951,0.0002719795],"domain_scores_gemma":[0.9994653,0.0001398396,0.0001295501,0.00006656476,0.0000261745,0.0001725575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002647747,0.000008203289,0.01668655,0.000003544443,0.00001323404,2.512278e-7,0.0001408594,0.000001066684,0.958349,0.00005902728,0.00002071104,0.0246911],"study_design_scores_gemma":[0.0002499489,0.0008509866,0.643695,0.00003504541,0.00002837957,0.000004399432,0.00009090119,0.008036162,0.3420538,0.002040859,0.002471694,0.000442849],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987838,0.00001531337,0.00001708736,0.0005449997,0.00008460001,0.0002165874,0.0001869286,0.00006898967,0.00008169354],"genre_scores_gemma":[0.9980853,0.00001780775,0.00008446223,0.0004528927,0.0005885315,0.00002159284,0.0006926678,0.000002225054,0.00005457542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6270084,"threshold_uncertainty_score":0.3518856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009262650152960529,"score_gpt":0.1939275293163471,"score_spread":0.1846648791633866,"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."}}