{"id":"W2911600539","doi":"10.1002/pra2.2018.14505501073","title":"Peer review, bibliometrics and altmetrics ‐ Do we need them all?","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Altmetrics; Bibliometrics; Citation; Science Citation Index; Computer science; Impact factor; Proxy (statistics); Quality (philosophy); Social media; Data science; Toolbox; Data mining; 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":[{"model":"gemma","categories":["metaresearch","bibliometrics"],"domain":"evaluation","study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics","metaresearch"],"domain":"evaluation","study_design":"not_applicable","genre":"commentary","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.1617095,0.001284917,0.003124851,0.01291994,0.005587914,0.03193315,0.003997547,0.01180487,0.007276332],"category_scores_gemma":[0.3902564,0.0006849183,0.001384814,0.0193435,0.02665744,0.05890622,0.007848307,0.01438617,0.004937268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01033447,"about_ca_system_score_gemma":0.02067173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005710026,"about_ca_topic_score_gemma":0.004146648,"domain_scores_codex":[0.8407887,0.08935816,0.009035562,0.007081197,0.05102955,0.00270687],"domain_scores_gemma":[0.5659623,0.2260523,0.01915165,0.017983,0.1632136,0.007637168],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006482111,0.00005307176,0.001643501,0.002604565,0.000136134,0.00008411595,0.003807442,0.0003695762,0.0002269953,0.2522182,0.4512875,0.2875041],"study_design_scores_gemma":[0.00002835669,0.00005136168,0.002045763,0.005071699,0.00004470997,0.000135128,0.005877828,0.0006715565,0.0002939032,0.2057361,0.7798846,0.0001589782],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.000683418,0.1080379,0.006098742,0.8559799,0.01973061,0.00006207829,0.00009058847,0.0001537495,0.009163035],"genre_scores_gemma":[0.1401832,0.4116681,0.02986994,0.233316,0.1629186,0.0007063439,0.0004551036,0.0008790558,0.02000385],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.98708,"threshold_uncertainty_score":0.8552118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2820165169104853,"score_gpt":0.4876526026311676,"score_spread":0.2056360857206823,"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."}}