{"id":"W3024612087","doi":"10.3390/su12103997","title":"A Bibliometric Analysis on No-Show Research: Status, Hotspots, Trends and Outlook","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Healthcare Operations and Scheduling Optimization","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Humanities and Social Science Fund of Ministry of Education of China; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Sustainability; Scope (computer science); Bibliometrics; Service (business); Regional science; Web of science; Institution; Political science; Position (finance); Business; Library science; Marketing; Computer science; Geography; Social science; Sociology; MEDLINE","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.009837842,0.0008698344,0.001901648,0.1200728,0.001929943,0.009137412,0.0009571197,0.0009061081,0.004562383],"category_scores_gemma":[0.03171134,0.0002909678,0.001887222,0.2211418,0.001149077,0.006975647,0.002404452,0.0006835421,0.001057614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003158815,"about_ca_system_score_gemma":0.004867399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005452082,"about_ca_topic_score_gemma":0.007419812,"domain_scores_codex":[0.9879792,0.002525663,0.002061899,0.001075787,0.005730668,0.0006268055],"domain_scores_gemma":[0.9525152,0.02225838,0.009383989,0.002385643,0.01216885,0.001287915],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002468941,0.0001609693,0.2692042,0.02193441,0.001387346,0.0006081953,0.004082115,0.001863846,0.002028709,0.02157201,0.04409905,0.6328123],"study_design_scores_gemma":[0.00004644674,0.000316675,0.6614426,0.01011985,0.002255866,0.001908173,0.01713731,0.008690544,0.003739746,0.02165373,0.2723939,0.0002952327],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3860442,0.3943642,0.02850634,0.03110649,0.002845163,0.001080203,0.05586714,0.001799197,0.09838712],"genre_scores_gemma":[0.7951136,0.1541894,0.01480736,0.0009230381,0.002447717,0.0006229877,0.02551129,0.0001984603,0.006186005],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9901621,"threshold_uncertainty_score":0.05202806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1769485425485671,"score_gpt":0.5096127844642165,"score_spread":0.3326642419156494,"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."}}