{"id":"W7039123704","doi":"","title":"LDOW 2016, Linked Data on the Web. Online resource: Proceedings of the Workshop on Linked Data on the Web co-located with 25th International World Wide Web Conference (WWW 2016), Montreal, Canada, April 12th, 2016","year":2016,"lang":"en","type":"other","venue":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Linked data; Semantic Web; The Internet; Real world data; RDF; Web standards","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009916169,0.002330019,0.001802136,0.006421795,0.002857746,0.01253876,0.003746985,0.003282304,0.08815432],"category_scores_gemma":[0.03097341,0.001865827,0.001512219,0.009130092,0.001672202,0.01702102,0.01011917,0.005577553,0.07758196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002963287,"about_ca_system_score_gemma":0.008969974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05478223,"about_ca_topic_score_gemma":0.06661963,"domain_scores_codex":[0.9954464,0.001056387,0.000642841,0.0004763507,0.001986386,0.0003916596],"domain_scores_gemma":[0.9821215,0.004932032,0.0008055579,0.005179183,0.003433304,0.003528336],"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":[0.0001482752,0.00007497147,0.0004806874,0.0005323503,0.0000258252,0.00009143796,0.0002553598,0.0002753207,0.001055179,0.01458072,0.9427524,0.03972748],"study_design_scores_gemma":[0.00006205843,0.00001557019,0.001207959,0.0003853246,0.00001823065,0.00006696404,0.0001636807,0.001065608,0.001412234,0.0107012,0.9848496,0.00005153398],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003058081,0.00782337,0.123736,0.01989238,0.005424388,0.001175522,0.5870011,0.1333367,0.1185526],"genre_scores_gemma":[0.009720748,0.005697824,0.0502503,0.002122997,0.001088051,0.0007975487,0.785162,0.03686882,0.1082917],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.08815432,"threshold_uncertainty_score":0.2949055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05120122048843657,"score_gpt":0.2819916134665579,"score_spread":0.2307903929781214,"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."}}