{"id":"W2394801617","doi":"","title":"Is there a gender gap in social media metrics","year":2015,"lang":"en","type":"article","venue":"ISSI","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Social media; Altmetrics; Citation; Visibility; Dissemination; Public relations; Sociology; Social science; Political science; Geography; Data science; Library science; Computer science","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.02202918,0.0003136565,0.0007734483,0.005539007,0.0007460453,0.003919295,0.0009134484,0.0007197017,0.007805358],"category_scores_gemma":[0.1401713,0.0002035317,0.0007333932,0.006296507,0.001435267,0.004718226,0.002541848,0.0006132427,0.001884636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001112011,"about_ca_system_score_gemma":0.001343929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00273652,"about_ca_topic_score_gemma":0.002714678,"domain_scores_codex":[0.9851035,0.005646204,0.00139754,0.00160872,0.005207158,0.001036867],"domain_scores_gemma":[0.8865811,0.07018378,0.02078494,0.005299104,0.01438864,0.002762429],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000760613,0.0001690796,0.7182458,0.001233443,0.0005262209,0.0002320063,0.02030988,0.0001681939,0.001103517,0.01656362,0.01100977,0.2296779],"study_design_scores_gemma":[0.00005037234,0.0005165804,0.8809584,0.00176909,0.0002635134,0.0007335611,0.02493646,0.0009368745,0.002030499,0.02114952,0.06656874,0.00008639223],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.859405,0.01836583,0.009848325,0.0291517,0.001255367,0.0002319928,0.007835484,0.0001634744,0.07374286],"genre_scores_gemma":[0.9919949,0.001743885,0.001491131,0.001232904,0.0003250446,0.0001491946,0.001080369,0.00007258543,0.001910045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.994461,"threshold_uncertainty_score":0.1165028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9068326217978037,"score_gpt":0.6403701424126986,"score_spread":0.266462479385105,"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."}}