{"id":"W4211045182","doi":"10.1142/s1793351x07000081","title":"GUEST EDITOR'S INTRODUCTION","year":2007,"lang":"en","type":"article","venue":"International Journal of Semantic Computing","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Ping (video games); Computer science; Download; World Wide Web; Information retrieval; Library science; Multimedia; Computer security","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":[0.001477602,0.00009921507,0.0001683576,0.0003299993,0.00006091503,0.0001778454,0.001263339,0.00004449076,0.000008021751],"category_scores_gemma":[0.0003476885,0.00008564613,0.0001055465,0.0001747403,0.00003945075,0.0004853126,0.0002373998,0.0002120482,0.0000190527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008307266,"about_ca_system_score_gemma":0.0000555631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001364692,"about_ca_topic_score_gemma":0.000004997149,"domain_scores_codex":[0.9983232,0.00002847473,0.0005988827,0.0001597449,0.0006838957,0.0002058059],"domain_scores_gemma":[0.9982616,0.0002648256,0.0004921681,0.0001667682,0.0007478715,0.0000667273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001908154,0.0007054915,0.04214123,0.00004734108,0.0008862345,0.002590433,0.005158728,0.002574134,0.01744838,0.101942,0.1402427,0.6860725],"study_design_scores_gemma":[0.006063719,0.001232729,0.2703406,0.00103411,0.0001313254,0.02096169,0.002704946,0.1216066,0.07238494,0.0278114,0.4739544,0.001773589],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1050934,0.0001338798,0.8238555,0.005748687,0.06462078,0.00002878548,1.200396e-7,0.00005185529,0.0004669635],"genre_scores_gemma":[0.9140949,0.00001212642,0.03663887,0.0001835502,0.04903493,4.732569e-8,4.563644e-7,0.000004886575,0.00003024004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8090015,"threshold_uncertainty_score":0.3492548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00949564057819452,"score_gpt":0.2784036438468258,"score_spread":0.2689080032686313,"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."}}