{"id":"W6928996209","doi":"10.4230/dagrep.12.9.60","title":"Knowledge Graphs and their Role in the Knowledge Engineering of the 21st Century (Dagstuhl Seminar 22372)","year":2023,"lang":"en","type":"report","venue":"UvA-DARE (University of Amsterdam)","topic":"Cancer therapeutics and mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Knowledge engineering; Knowledge graph; Generative grammar; Knowledge extraction; Sociology of scientific knowledge; Snapshot (computer storage); Natural language; Knowledge representation and reasoning; Knowledge integration; Domain knowledge","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003922837,0.0002556749,0.0003604972,0.0001511789,0.0001006953,0.00001095724,0.0006391986,0.0003201507,0.000009987662],"category_scores_gemma":[0.00001933345,0.0002021831,0.0002726025,0.0003060986,0.0001405526,0.000004891385,0.0005380882,0.0002623089,0.000001940315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005278453,"about_ca_system_score_gemma":0.0003252366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002533225,"about_ca_topic_score_gemma":0.001426669,"domain_scores_codex":[0.9989781,0.00007551074,0.0001796149,0.0003536226,0.0001769319,0.0002361619],"domain_scores_gemma":[0.9989488,0.00004046611,0.0002103243,0.0005717128,0.0001827443,0.00004595804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003891698,0.001030088,0.002034098,0.004728345,0.002283638,0.00005019464,0.04782225,0.00008288719,0.715048,0.004019401,0.01318083,0.2093312],"study_design_scores_gemma":[0.001098942,0.0003968383,0.008680017,0.000975707,0.0002510683,0.00005639959,0.02572296,0.0001492041,0.0153995,0.0002542925,0.946389,0.0006261102],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8987354,0.06419217,0.00009547753,0.0002599581,0.00220791,0.001253776,0.0008790783,0.00004718502,0.03232905],"genre_scores_gemma":[0.9759353,0.02077745,0.00003061089,0.00001857311,0.0001114886,0.000002183485,0.0001090191,0.0000457645,0.002969627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9332081,"threshold_uncertainty_score":0.824479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02205700636785374,"score_gpt":0.2410056106041138,"score_spread":0.2189486042362601,"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."}}