{"id":"W1589942743","doi":"10.1007/b102467","title":"The SemanticWeb – ISWC 2004: Third International SemanticWeb Conference Hiroshima, Japan, November 7-11, 2004 Proceedings","year":2004,"lang":"en","type":"article","venue":"VU Research Portal","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Social Semantic Web; Semantic Web Stack; World Wide Web; OWL-S; Semantic analytics; Semantic Web; Semantic Web Rule Language; Data Web; Information retrieval; Semantic grid; Web standards; Web service","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":[0.004175487,0.0009008255,0.001362491,0.00222305,0.00269133,0.006280527,0.001878495,0.001910557,0.02506606],"category_scores_gemma":[0.003465325,0.0008405148,0.0008549849,0.00470156,0.001935348,0.007605693,0.002156602,0.002326885,0.01158533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003648725,"about_ca_system_score_gemma":0.009954837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0521473,"about_ca_topic_score_gemma":0.05230575,"domain_scores_codex":[0.9990457,0.00024825,0.00008346836,0.0001670566,0.0003302081,0.0001252255],"domain_scores_gemma":[0.996307,0.0004027799,0.0001579608,0.0005937306,0.001724975,0.0008135587],"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":[0.0005949546,0.0005194296,0.003618089,0.0005475383,0.0001545378,0.0004155168,0.001191404,0.001640549,0.01028236,0.02714203,0.7528636,0.20103],"study_design_scores_gemma":[0.00009155239,0.0000990501,0.007262397,0.0003257169,0.0002274118,0.0003648368,0.001370223,0.008628011,0.0113418,0.0162393,0.9539812,0.00006861988],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1616392,0.04998952,0.3697996,0.07325161,0.03248315,0.001765985,0.01940587,0.024074,0.2675911],"genre_scores_gemma":[0.1811134,0.02762056,0.173641,0.004737271,0.002830549,0.0007708101,0.0770456,0.00716908,0.5250717],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0521473,"threshold_uncertainty_score":0.1036875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06068194803944819,"score_gpt":0.3433344280454715,"score_spread":0.2826524800060233,"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."}}