{"id":"W4310896317","doi":"10.1016/j.heliyon.2022.e12181","title":"Knowledge mapping of population health: A bibliometric analysis","year":2022,"lang":"en","type":"article","venue":"Heliyon","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Postdoctoral Science Foundation","keywords":"Population; Bibliometrics; Population health; Status quo; Political science; Geography; Social science; Library science; Medicine; Sociology; Environmental health; Computer science; Law","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.007103619,0.0006072272,0.001300201,0.1378115,0.00228954,0.006475483,0.0008390745,0.0007143806,0.00457866],"category_scores_gemma":[0.03049365,0.0002970072,0.001701338,0.1733301,0.0009700791,0.004480676,0.002811642,0.0004700417,0.0006568055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003367117,"about_ca_system_score_gemma":0.004555143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008159802,"about_ca_topic_score_gemma":0.007449155,"domain_scores_codex":[0.9905933,0.002581684,0.001157109,0.0007199601,0.004646032,0.0003019273],"domain_scores_gemma":[0.9842929,0.01066083,0.001682153,0.0008025504,0.002355637,0.0002058354],"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":[0.0001539821,0.0002864156,0.2448438,0.007408347,0.001507047,0.000769703,0.008956031,0.009489768,0.001751963,0.04098099,0.02356498,0.660287],"study_design_scores_gemma":[0.0001032114,0.0003986202,0.636094,0.003411821,0.002142398,0.001835641,0.03417905,0.090909,0.003673692,0.07884733,0.1480556,0.0003495522],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7071086,0.02296816,0.08885677,0.008005153,0.000453502,0.002593303,0.04654184,0.001628333,0.1218444],"genre_scores_gemma":[0.9205588,0.01101785,0.05266473,0.0001147863,0.0003037234,0.001119701,0.01089597,0.00009593744,0.003228369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8621885,"threshold_uncertainty_score":0.03756797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08690656072275363,"score_gpt":0.4037187720645823,"score_spread":0.3168122113418287,"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."}}