{"id":"W3129446086","doi":"10.1108/lhtn-11-2020-0106","title":"ORCID education: a departmental approach","year":2021,"lang":"en","type":"article","venue":"Library Hi Tech News","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Outreach; Context (archaeology); Promotion (chess); Library science; Computer science; Political science; History","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02967678,0.000441454,0.0004209085,0.004266753,0.01552038,0.01583441,0.006062474,0.002945828,0.05076528],"category_scores_gemma":[0.03921787,0.000586241,0.000607836,0.006098554,0.007268838,0.007378422,0.02291996,0.006248675,0.007604081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0286224,"about_ca_system_score_gemma":0.07147373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009054913,"about_ca_topic_score_gemma":0.02387738,"domain_scores_codex":[0.9629739,0.01986028,0.001584661,0.003174963,0.006973514,0.00543276],"domain_scores_gemma":[0.932873,0.01347088,0.003850447,0.006078493,0.01492419,0.02880293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002631126,0.002905924,0.0369769,0.001006619,0.00005211757,0.001522365,0.03231155,0.0006885861,0.002138087,0.1871969,0.2072136,0.5277243],"study_design_scores_gemma":[0.0001131289,0.0005156505,0.01344998,0.0006619161,0.00003289422,0.0008005283,0.06354146,0.001151624,0.001610565,0.02612537,0.8919058,0.00009104098],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1553675,0.002030304,0.06602241,0.1763378,0.005476866,0.003878078,0.0008183902,0.003218831,0.5868498],"genre_scores_gemma":[0.7530667,0.001040119,0.0560726,0.03816287,0.0009667108,0.002043424,0.0005336964,0.0007092012,0.1474048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9841656,"threshold_uncertainty_score":0.207671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4620305300491584,"score_gpt":0.5378759009917609,"score_spread":0.07584537094260246,"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."}}