{"id":"W6912383844","doi":"10.5281/zenodo.4007855","title":"Metrics Literacies: Improving Understanding and Use of Scholarly Metrics In Academia","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Dissemination; Presentation (obstetrics); Set (abstract data type); Information Dissemination; Test (biology); Scholarly communication; Unit (ring theory)","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008529085,0.00008817665,0.0001271878,0.000577246,0.0006243618,0.003025149,0.0009085574,0.0001058584,0.0002760601],"category_scores_gemma":[0.004979137,0.00009666506,0.0000223309,0.003170636,0.00005693249,0.002834989,0.001463187,0.0008589237,0.0001950019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001604806,"about_ca_system_score_gemma":0.000008298885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001766228,"about_ca_topic_score_gemma":8.365277e-8,"domain_scores_codex":[0.998553,0.0002777794,0.0002578497,0.0003404102,0.0003470407,0.0002239431],"domain_scores_gemma":[0.999074,0.0001084407,0.0001294261,0.0002008052,0.000300991,0.0001862765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009258927,0.0002671039,0.002059304,0.0005559319,0.00007569044,0.00003369683,0.06380707,0.000763239,0.0198785,0.4738618,0.03054443,0.4080607],"study_design_scores_gemma":[0.0009888393,0.0005036397,0.004646094,0.00008370615,0.00001392025,0.00004444481,0.009190686,0.08588357,0.0009657316,0.0006256637,0.8966216,0.0004321314],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1527,0.0005925184,0.7778078,0.01618031,0.0002910032,0.0009898173,0.00004053238,0.001328829,0.0500692],"genre_scores_gemma":[0.9933166,0.0001215333,0.005807247,0.0004076594,0.00002834381,1.206251e-8,0.00003089341,0.0001981769,0.00008956578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8660771,"threshold_uncertainty_score":0.9980098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1324380687666445,"score_gpt":0.2829660303958512,"score_spread":0.1505279616292067,"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."}}