{"id":"W3041666820","doi":"","title":"Subject Guides: Vancouver - Referencing Guide: Abbreviations","year":2019,"lang":"en","type":"libguides","venue":"","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Subject (documents); Computer science; History; World Wide Web","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":[0.002065561,0.001815532,0.001829807,0.008686761,0.002590129,0.008002188,0.002627503,0.002166132,0.6899614],"category_scores_gemma":[0.01363486,0.0008985008,0.0007144664,0.008988958,0.000909137,0.004206466,0.002527893,0.002294556,0.6636651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004831313,"about_ca_system_score_gemma":0.009773381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04939433,"about_ca_topic_score_gemma":0.104617,"domain_scores_codex":[0.9980614,0.0002776814,0.0001964539,0.000251763,0.001024536,0.0001882114],"domain_scores_gemma":[0.9872051,0.001199214,0.0003024583,0.0007992819,0.009523161,0.0009707451],"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":[0.000006752685,0.000007616266,0.00004681775,0.00009053813,5.251482e-7,0.000007158628,0.00001467918,0.00003677049,0.00003363057,0.001333073,0.978027,0.02039534],"study_design_scores_gemma":[0.000003113816,0.000002746676,0.0002276336,0.0001091202,8.70948e-7,0.0000149792,0.00003478382,0.00005224605,0.00006940645,0.0009806365,0.9984995,0.000005000259],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000265774,0.002104295,0.004011858,0.003140566,0.007669775,0.0006468029,0.04151162,0.004136918,0.9365124],"genre_scores_gemma":[0.0007726465,0.001244299,0.00263449,0.0004244134,0.0006233377,0.0003076953,0.01703358,0.001881041,0.9750783],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9919978,"threshold_uncertainty_score":0.4422324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06159688449064771,"score_gpt":0.2383969142019654,"score_spread":0.1768000297113177,"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."}}