{"id":"W458847379","doi":"","title":"Research Guides. Vancouver Citation Style Guide. Drug Information Databases.","year":2013,"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":"Database; Citation; Style (visual arts); Computer science; Information retrieval; World Wide Web; Data science; Geography; 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":[0.002816329,0.002040067,0.003988105,0.02603974,0.001496422,0.006118065,0.004462534,0.002285451,0.5521702],"category_scores_gemma":[0.02081488,0.001727773,0.001164224,0.05321127,0.0007442172,0.003454336,0.001656118,0.00260595,0.4681166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00447265,"about_ca_system_score_gemma":0.01575631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09107505,"about_ca_topic_score_gemma":0.1749517,"domain_scores_codex":[0.9966149,0.0004106467,0.0006224362,0.0003809521,0.001766897,0.0002042784],"domain_scores_gemma":[0.9746479,0.005210962,0.001614491,0.001621851,0.01487366,0.002031093],"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":[0.0000209815,0.000010057,0.00006282285,0.0009142947,0.00000610833,0.00000677886,0.000009570745,0.00003675856,0.00003526087,0.0007536698,0.9651235,0.03302022],"study_design_scores_gemma":[0.00001927516,0.00001039046,0.0005839145,0.000538596,0.00001124297,0.0000196465,0.0000186078,0.00005407053,0.00009335141,0.0009748131,0.9976643,0.00001170351],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0001849823,0.01287449,0.001783506,0.003251307,0.0009593337,0.0005116668,0.7263887,0.005317442,0.2487286],"genre_scores_gemma":[0.002014565,0.03573855,0.01036249,0.002128381,0.0009056375,0.001250978,0.5199496,0.003460405,0.4241894],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9938819,"threshold_uncertainty_score":0.6387749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1081709997460293,"score_gpt":0.2888754707925917,"score_spread":0.1807044710465623,"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."}}