{"id":"W2950851292","doi":"10.48550/arxiv.1705.03258","title":"Measuring Social Media Activity of Scientific Literature: An Exhaustive Comparison of Scopus and Novel Altmetrics Big Data","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Scopus; Altmetrics; Social media; Citation; Negative binomial distribution; Count data; Computer science; Statistics; Information retrieval; Data science; Library science; Mathematics; MEDLINE; World Wide Web; Political 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":[0.005589434,0.0007127492,0.0007996644,0.04353005,0.0006790102,0.00360101,0.0006903885,0.0005937248,0.001615507],"category_scores_gemma":[0.03035312,0.0001886024,0.0009236187,0.04860565,0.0005165469,0.003364287,0.00211974,0.0003878022,0.0009271385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006026217,"about_ca_system_score_gemma":0.001331907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001675905,"about_ca_topic_score_gemma":0.004024421,"domain_scores_codex":[0.9924119,0.001139073,0.001563146,0.0006220021,0.003943944,0.0003199611],"domain_scores_gemma":[0.9580119,0.016641,0.01387545,0.002411484,0.00755441,0.001505829],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003804813,0.0002998863,0.731192,0.004677662,0.000813154,0.0006813115,0.001646272,0.002135592,0.004742617,0.00390099,0.01227863,0.2372514],"study_design_scores_gemma":[0.00003172039,0.000417898,0.9365036,0.0009203533,0.0004400685,0.00125668,0.002900118,0.008839788,0.004280781,0.003803693,0.04049889,0.0001063933],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8743472,0.0133109,0.01124624,0.001457894,0.0002695023,0.0004418352,0.06672471,0.001366524,0.03083519],"genre_scores_gemma":[0.8951886,0.006140623,0.02186622,0.0002958028,0.0007228997,0.0006989526,0.07149883,0.0001706908,0.003417472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9944106,"threshold_uncertainty_score":0.02956015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9146932420703743,"score_gpt":0.4782998300848035,"score_spread":0.4363934119855707,"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."}}