{"id":"W3006223058","doi":"","title":"LibGuides: Vancouver Referencing Style: Images, maps, tables, etc.","year":2019,"lang":"en","type":"libguides","venue":"","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Style (visual arts); Table (database); Computer science; Computer graphics (images); Computer vision; Artificial intelligence; Cartography; Information retrieval; Geography; Data mining; Archaeology","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":["scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000868323,0.001012573,0.0005343854,0.0075267,0.005459484,0.01038872,0.0009637512,0.001372421,0.3166542],"category_scores_gemma":[0.003686392,0.0003766115,0.0001873181,0.01471211,0.002105094,0.003345289,0.002413144,0.001890019,0.1053391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00833592,"about_ca_system_score_gemma":0.01002376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3267595,"about_ca_topic_score_gemma":0.5366826,"domain_scores_codex":[0.9990228,0.000137181,0.00006308916,0.0001246582,0.0005579513,0.00009422948],"domain_scores_gemma":[0.9977478,0.0002199921,0.00007979796,0.0001558859,0.001499713,0.0002967898],"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":[0.00002744004,0.000007759631,0.000397704,0.0003229191,0.000002669315,0.00006617651,0.001708436,0.00005576342,0.0001560685,0.02289569,0.8652283,0.1091311],"study_design_scores_gemma":[0.000001385879,0.000002185077,0.0008719716,0.0002203993,0.000001102952,0.00005637754,0.0008268095,0.00002331661,0.0001044122,0.001253553,0.9966335,0.000005119864],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001609875,0.007845267,0.0009305087,0.003292065,0.002144509,0.00004831199,0.00892665,0.0009678372,0.9742349],"genre_scores_gemma":[0.01594174,0.005957421,0.001638553,0.000437774,0.0003391115,0.00005799046,0.005705276,0.0011085,0.9688136],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9896113,"threshold_uncertainty_score":0.9747098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0279049357004987,"score_gpt":0.2328720165940447,"score_spread":0.204967080893546,"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."}}