{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01667754,0.001340704,0.000930644,0.002326555,0.003501194,0.0118011,0.001889951,0.004588658,0.02908897],"category_scores_gemma":[0.01372868,0.0007414515,0.001104845,0.002052171,0.004950903,0.00682742,0.008950936,0.006255489,0.0120137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008484882,"about_ca_system_score_gemma":0.007635728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003888046,"about_ca_topic_score_gemma":0.004509471,"domain_scores_codex":[0.990999,0.004361551,0.0003145764,0.001036049,0.001850713,0.001438148],"domain_scores_gemma":[0.9941356,0.002518737,0.0002457111,0.0003379409,0.0009002102,0.001861788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002189005,0.0001606054,0.0002038636,0.0002783243,0.00002738806,0.0002469544,0.00282601,0.001763081,0.001090254,0.3053781,0.5813856,0.1064209],"study_design_scores_gemma":[0.00003342987,0.00004492436,0.0004425389,0.0002968596,0.000009257114,0.00007835634,0.000698245,0.0007006657,0.0005630603,0.09426227,0.9028357,0.00003463509],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.02032788,0.08187909,0.05948869,0.5880863,0.05947145,0.000409509,0.002355845,0.001438225,0.1865431],"genre_scores_gemma":[0.2797559,0.04589793,0.08161699,0.04389648,0.02373199,0.001319669,0.004050342,0.003319228,0.5164115],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02908897,"threshold_uncertainty_score":0.09731233,"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."}}