{"id":"W6939856199","doi":"10.6084/m9.figshare.c.3882952.v1","title":"Applications of altmetrics for Canadian institutions","year":2017,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Altmetrics; Social media; Citizen science; Field (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch","bibliometrics"],"domain":"evaluation","study_design":"not_applicable","genre":"other","about_ca_system":true,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":true,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003628349,0.001203252,0.0005395755,0.01093888,0.005313591,0.006469233,0.001986777,0.001268155,0.3026998],"category_scores_gemma":[0.01535736,0.0006917185,0.0009786679,0.02289066,0.001386827,0.003798759,0.003837136,0.001964009,0.1154196],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02227814,"about_ca_system_score_gemma":0.04371627,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8971774,"about_ca_topic_score_gemma":0.9543614,"domain_scores_codex":[0.9954295,0.0002315518,0.0001204787,0.0002092919,0.003506109,0.0005031188],"domain_scores_gemma":[0.9828103,0.001266642,0.0003719266,0.00107781,0.01234048,0.002132863],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007581061,0.000004608585,0.0003062976,0.00004809227,0.000001719219,0.00002400481,0.0001081761,0.00006752172,0.00008651063,0.002431533,0.9708768,0.02603726],"study_design_scores_gemma":[0.000002508668,0.000001678693,0.001936617,0.00008364282,0.000001926264,0.00002477866,0.0001861765,0.0001240846,0.0001020998,0.0006747748,0.9968437,0.0000179886],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001762384,0.002719506,0.007657836,0.01667874,0.002894806,0.0005150721,0.1590693,0.01608035,0.792622],"genre_scores_gemma":[0.02293159,0.009444308,0.03436169,0.003453588,0.001586866,0.0004540667,0.1115494,0.01275106,0.8034675],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9963716,"threshold_uncertainty_score":0.9946141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1615220311732184,"score_gpt":0.3609200532399597,"score_spread":0.1993980220667413,"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."}}