{"id":"W2955631702","doi":"10.1111/cid.12810","title":"The funding sources of implantology research in the period 2008‐2017: A bibliometric analysis","year":2019,"lang":"en","type":"article","venue":"Clinical Implant Dentistry and Related Research","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dentistry; Bibliometrics; Citation; Scopus; Government (linguistics); Citation analysis; Medicine; Subject (documents); Commercialization; Library science; Dental research; Web of science; Period (music); MEDLINE; Political science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics","metaresearch"],"domain":"incentives","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics","metaresearch"],"domain":"incentives","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","bibliometrics","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","bibliometrics","sts"],"category_scores_codex":[0.2984419,0.0001910869,0.000829983,0.397072,0.001551329,0.003469553,0.006026392,0.0006421983,0.0003884048],"category_scores_gemma":[0.06210956,0.00008957701,0.0004502801,0.814755,0.002985573,0.0003361538,0.002195679,0.00411034,0.00101366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005269462,"about_ca_system_score_gemma":0.0003972629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003796823,"about_ca_topic_score_gemma":0.0001791257,"domain_scores_codex":[0.9670802,0.01141216,0.002659802,0.00147754,0.01513111,0.002239201],"domain_scores_gemma":[0.8515741,0.1417635,0.0004368318,0.001944751,0.003723146,0.000557624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002522648,0.0003655972,0.9034712,0.00002861068,0.0003913205,0.003257838,0.0002909349,0.00002150193,0.0001370494,0.002036522,0.02079128,0.06895585],"study_design_scores_gemma":[0.0009252594,0.0006739248,0.9580829,0.00003204446,0.00003958302,0.004971016,0.005665898,0.002899367,0.00003902267,0.008317101,0.01818915,0.0001648109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802386,0.010014,0.00001738576,0.002638898,0.001828672,0.0006370386,0.00005770428,0.000008660878,0.004559039],"genre_scores_gemma":[0.9862344,0.009039131,0.00001944451,0.00001837126,0.00007476049,0.00002092494,0.00001036174,0.00001008586,0.004572503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4176829,"threshold_uncertainty_score":0.9997641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7769852019218009,"score_gpt":0.6830523692882974,"score_spread":0.0939328326335035,"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."}}