{"id":"W2765946894","doi":"","title":"Mobile computing: a scientometric assessment of global publications output","year":2017,"lang":"en","type":"article","venue":"Annals of Library and Information Studies (ALIS)","topic":"Satellite Communication Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citation impact; Scopus; Citation; China; Scientometrics; Library science; Political science; Geography; Business; Computer science; 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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.006166391,0.0007420329,0.0008901703,0.0676562,0.0009410093,0.003854609,0.000703514,0.0006335782,0.003253473],"category_scores_gemma":[0.02581906,0.0001868185,0.001575813,0.122149,0.0006014784,0.003239872,0.002383228,0.0004206993,0.001608571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358231,"about_ca_system_score_gemma":0.002175363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003372456,"about_ca_topic_score_gemma":0.002625523,"domain_scores_codex":[0.9920686,0.001281617,0.0009521201,0.0004383891,0.004826836,0.0004324277],"domain_scores_gemma":[0.9818518,0.005919717,0.004024411,0.001245251,0.006244968,0.0007138083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002109308,0.0002187689,0.690977,0.002269964,0.0007981934,0.0005928713,0.002618814,0.004220338,0.001260559,0.006723983,0.02308875,0.2670198],"study_design_scores_gemma":[0.00002613128,0.0004229086,0.9136349,0.0004752725,0.0003349496,0.0009321464,0.005681027,0.008435505,0.001395917,0.003166203,0.06542699,0.00006809691],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8464767,0.01024072,0.007758141,0.00191958,0.000363321,0.0007381305,0.05063872,0.0008207095,0.08104401],"genre_scores_gemma":[0.9453366,0.007451694,0.006147426,0.0001429899,0.0005734319,0.0006138772,0.03439191,0.0001426393,0.005199463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9323438,"threshold_uncertainty_score":0.03261137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.133052951974665,"score_gpt":0.3952346011275661,"score_spread":0.2621816491529011,"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."}}