{"id":"W2571324080","doi":"10.1371/journal.pone.0168597","title":"Bibliometrics for Social Validation","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Office of Research and Development; U.S. Environmental Protection Agency","keywords":"Bibliometrics; Data science; Agency (philosophy); Computer science; Citation; Social network analysis; Management science; Social science; Data mining; Sociology; Social media; Library science; World Wide Web; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.06005038,0.002659978,0.00385876,0.09707778,0.004372204,0.0139153,0.003857736,0.003035064,0.01358648],"category_scores_gemma":[0.3451687,0.001085114,0.002892164,0.1116697,0.007027879,0.01619346,0.009000324,0.003314196,0.004064307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006938947,"about_ca_system_score_gemma":0.007755651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006728488,"about_ca_topic_score_gemma":0.00361821,"domain_scores_codex":[0.8706947,0.06985915,0.01126723,0.01022681,0.03661494,0.001337183],"domain_scores_gemma":[0.634365,0.2628576,0.032937,0.04111594,0.02660205,0.002122278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001617392,0.0001576217,0.0224545,0.004352866,0.001490514,0.0002643791,0.002527526,0.01482332,0.0005322804,0.598219,0.03670297,0.3183134],"study_design_scores_gemma":[0.00008918978,0.00007304855,0.01617819,0.001427326,0.0003143307,0.0003975008,0.001609618,0.04353936,0.001016058,0.7675337,0.1675858,0.0002359183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02741336,0.01881572,0.7579606,0.01379372,0.00277105,0.002472671,0.03484502,0.006475943,0.1354519],"genre_scores_gemma":[0.5274371,0.01104299,0.4111208,0.00191439,0.004140457,0.009426239,0.02247726,0.001507105,0.01093364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9029222,"threshold_uncertainty_score":0.3175806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2008511291881503,"score_gpt":0.341397473992494,"score_spread":0.1405463448043437,"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."}}