{"id":"W2051581953","doi":"10.1145/2064696.2064705","title":"Semantic text mining for lignocellulose research","year":2011,"lang":"en","type":"article","venue":"","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Génome Québec; Genome Canada","keywords":"Computer science; Semantic Web; Identification (biology); Social Semantic Web; World Wide Web; Semantic analytics; Ontology; Semantic Web Stack; Interface (matter); Semantics (computer science); Data science; Information retrieval","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004034079,0.0007533894,0.0007712006,0.01161202,0.0016114,0.002614281,0.001070347,0.0009174769,0.003395552],"category_scores_gemma":[0.00950956,0.000354262,0.001424738,0.009477683,0.001030017,0.004584169,0.00162435,0.0009350539,0.001519149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001516479,"about_ca_system_score_gemma":0.003940001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002244702,"about_ca_topic_score_gemma":0.003326204,"domain_scores_codex":[0.9974552,0.0009097262,0.0006081863,0.0003282384,0.0006331893,0.00006546381],"domain_scores_gemma":[0.9950703,0.002619178,0.0005846004,0.0005944961,0.0009883745,0.0001430916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002790384,0.0004247344,0.004483894,0.005510867,0.0002698744,0.001420652,0.001253125,0.01367908,0.03077259,0.1160069,0.03400589,0.7918934],"study_design_scores_gemma":[0.0001430454,0.000149273,0.00650169,0.001553827,0.0003726038,0.001595192,0.001873694,0.2016679,0.05583248,0.3983002,0.3318608,0.0001493314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02608618,0.007636612,0.9234854,0.004981354,0.0003229548,0.00133769,0.01649022,0.009478343,0.01018128],"genre_scores_gemma":[0.0659817,0.004224849,0.9030245,0.0003522247,0.0001440254,0.0006339936,0.02386843,0.0002830167,0.001487264],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01161202,"threshold_uncertainty_score":0.02133447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1777350674694664,"score_gpt":0.3699209237205864,"score_spread":0.19218585625112,"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."}}