{"id":"W2898299795","doi":"10.1016/j.carbpol.2018.10.063","title":"The exopolysaccharide properties and structures database: EPS-DB. Application to bacterial exopolysaccharides","year":2018,"lang":"en","type":"article","venue":"Carbohydrate Polymers","topic":"Microbial Metabolites in Food Biotechnology","field":"Nursing","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"Cegep de Saint Hyacinthe; Agriculture and Agri-Food Canada","funders":"Agence Nationale de la Recherche","keywords":"Interoperability; Database; Computer science; Interface (matter); The Internet; World Wide Web; Information retrieval","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001502706,0.003255361,0.002066583,0.004551214,0.0007400682,0.003206052,0.003849076,0.001953298,0.03223971],"category_scores_gemma":[0.005882295,0.001156019,0.001607899,0.005500177,0.0004032005,0.002903881,0.003318002,0.001825837,0.02796304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005651814,"about_ca_system_score_gemma":0.001732028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002515803,"about_ca_topic_score_gemma":0.002271666,"domain_scores_codex":[0.9995136,0.00005277977,0.0001246181,0.000127795,0.0001368972,0.00004430836],"domain_scores_gemma":[0.9987838,0.0003442433,0.0001689057,0.0003131812,0.0001982978,0.0001916331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006414928,0.001036458,0.01518077,0.01323408,0.001289676,0.002146806,0.0006198148,0.009732401,0.04852354,0.01796262,0.6599602,0.2238987],"study_design_scores_gemma":[0.002174812,0.0005170002,0.01780471,0.001273574,0.0007746703,0.002399683,0.0004638044,0.04310027,0.04531085,0.02423348,0.8615423,0.0004047557],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01916981,0.004011721,0.05295818,0.0005339339,0.0002701656,0.0002871548,0.7937213,0.1172586,0.01178916],"genre_scores_gemma":[0.02812524,0.002331732,0.03959715,0.0002882436,0.0000657018,0.0003722669,0.9192057,0.006970113,0.003043763],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03223971,"threshold_uncertainty_score":0.1078526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01814196559412909,"score_gpt":0.2515961132788821,"score_spread":0.233454147684753,"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."}}